Overview

Dataset statistics

Number of variables62
Number of observations54
Missing cells1331
Missing cells (%)39.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.3 KiB
Average record size in memory498.4 B

Variable types

Numeric11
Categorical42
Unsupported9

Alerts

airdate has constant value "2020-12-20" Constant
rating.average has constant value "8.8" Constant
_embedded.show.network.officialSite has constant value "https://www.hbo.com/" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 54 distinct values High cardinality
name has a high cardinality: 54 distinct values High cardinality
_links.self.href has a high cardinality: 54 distinct values High cardinality
id is highly correlated with _embedded.show.network.idHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.network.idHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with _embedded.show.runtime and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 7 other fieldsHigh correlation
season is highly correlated with runtime and 2 other fieldsHigh correlation
runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.externals.thetvdb and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with _embedded.show.runtime and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 4 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.network.idHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with _embedded.show.runtime and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
id is highly correlated with url and 28 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 45 other fieldsHigh correlation
season is highly correlated with url and 26 other fieldsHigh correlation
number is highly correlated with url and 21 other fieldsHigh correlation
type is highly correlated with url and 17 other fieldsHigh correlation
airtime is highly correlated with url and 22 other fieldsHigh correlation
airstamp is highly correlated with url and 25 other fieldsHigh correlation
runtime is highly correlated with id and 38 other fieldsHigh correlation
summary is highly correlated with id and 31 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 40 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 26 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 33 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 28 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 32 other fieldsHigh correlation
image.medium is highly correlated with id and 37 other fieldsHigh correlation
image.original is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with url and 31 other fieldsHigh correlation
number has 2 (3.7%) missing values Missing
runtime has 5 (9.3%) missing values Missing
image has 54 (100.0%) missing values Missing
summary has 48 (88.9%) missing values Missing
rating.average has 53 (98.1%) missing values Missing
_embedded.show.runtime has 21 (38.9%) missing values Missing
_embedded.show.averageRuntime has 4 (7.4%) missing values Missing
_embedded.show.ended has 39 (72.2%) missing values Missing
_embedded.show.officialSite has 3 (5.6%) missing values Missing
_embedded.show.rating.average has 50 (92.6%) missing values Missing
_embedded.show.network has 54 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (3.7%) missing values Missing
_embedded.show.webChannel.name has 2 (3.7%) missing values Missing
_embedded.show.webChannel.country.name has 20 (37.0%) missing values Missing
_embedded.show.webChannel.country.code has 20 (37.0%) missing values Missing
_embedded.show.webChannel.country.timezone has 20 (37.0%) missing values Missing
_embedded.show.webChannel.officialSite has 34 (63.0%) missing values Missing
_embedded.show.dvdCountry has 54 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 54 (100.0%) missing values Missing
_embedded.show.externals.thetvdb has 13 (24.1%) missing values Missing
_embedded.show.externals.imdb has 27 (50.0%) missing values Missing
_embedded.show.image.medium has 3 (5.6%) missing values Missing
_embedded.show.image.original has 3 (5.6%) missing values Missing
_embedded.show.summary has 2 (3.7%) missing values Missing
_embedded.show._links.nextepisode.href has 49 (90.7%) missing values Missing
image.medium has 38 (70.4%) missing values Missing
image.original has 38 (70.4%) missing values Missing
_embedded.show.network.id has 49 (90.7%) missing values Missing
_embedded.show.network.name has 49 (90.7%) missing values Missing
_embedded.show.network.country.name has 49 (90.7%) missing values Missing
_embedded.show.network.country.code has 49 (90.7%) missing values Missing
_embedded.show.network.country.timezone has 49 (90.7%) missing values Missing
_embedded.show.network.officialSite has 53 (98.1%) missing values Missing
_embedded.show.webChannel has 54 (100.0%) missing values Missing
_embedded.show.image has 54 (100.0%) missing values Missing
_embedded.show.webChannel.country has 54 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 53 (98.1%) missing values Missing
_embedded.show.dvdCountry.code has 53 (98.1%) missing values Missing
_embedded.show.dvdCountry.timezone has 53 (98.1%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.rating.average is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
name has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.externals.tvrage is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.weight has 4 (7.4%) zeros Zeros

Reproduction

Analysis started2022-09-05 04:42:26.430091
Analysis finished2022-09-05 04:42:45.142434
Duration18.71 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2078343.759
Minimum1956340
Maximum2363744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:45.191850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1956340
5-th percentile1968453.4
Q11985393.25
median2024469.5
Q32153869.75
95-th percentile2363741.35
Maximum2363744
Range407404
Interquartile range (IQR)168476.5

Descriptive statistics

Standard deviation119686.6753
Coefficient of variation (CV)0.05758752599
Kurtosis0.3610501009
Mean2078343.759
Median Absolute Deviation (MAD)49548.5
Skewness1.135078188
Sum112230563
Variance1.432490023 × 1010
MonotonicityNot monotonic
2022-09-04T23:42:45.396981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20533501
 
1.9%
20053221
 
1.9%
19757461
 
1.9%
21117081
 
1.9%
19886231
 
1.9%
19670131
 
1.9%
19850261
 
1.9%
19968171
 
1.9%
19974261
 
1.9%
19975221
 
1.9%
Other values (44)44
81.5%
ValueCountFrequency (%)
19563401
1.9%
19565181
1.9%
19670131
1.9%
19692291
1.9%
19740531
1.9%
19740961
1.9%
19757461
1.9%
19773281
1.9%
19780131
1.9%
19816011
1.9%
ValueCountFrequency (%)
23637441
1.9%
23637431
1.9%
23637421
1.9%
23637411
1.9%
23181081
1.9%
22559851
1.9%
22346901
1.9%
21956021
1.9%
21785631
1.9%
21761371
1.9%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
https://www.tvmaze.com/episodes/2053350/ispoved-1x08-gnojnyj
 
1
https://www.tvmaze.com/episodes/2005322/laikykites-ten-5x15-sorosas-ir-kovidiotai-prekybos-centruose
 
1
https://www.tvmaze.com/episodes/1975746/friheden-2x06-afsnit-6
 
1
https://www.tvmaze.com/episodes/2111708/world-wonder-ring-stardom-2020-12-20-stardom-osaka-dream-cinderella
 
1
https://www.tvmaze.com/episodes/1988623/redakcia-s03-special-redakcia-news-putin-i-otravlenie-kleveta-v-internete-raznotyk
 
1
Other values (49)
49 

Length

Max length146
Median length98
Mean length84.51851852
Min length59

Characters and Unicode

Total characters4564
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2053350/ispoved-1x08-gnojnyj
2nd rowhttps://www.tvmaze.com/episodes/1956340/hero-return-1x11-episode-11
3rd rowhttps://www.tvmaze.com/episodes/1988863/swallowed-star-1x05-episode-5
4th rowhttps://www.tvmaze.com/episodes/2052510/wu-shen-zhu-zai-1x85-episode-85
5th rowhttps://www.tvmaze.com/episodes/2012322/mans-diary-2x07-episode-7

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2053350/ispoved-1x08-gnojnyj1
 
1.9%
https://www.tvmaze.com/episodes/2005322/laikykites-ten-5x15-sorosas-ir-kovidiotai-prekybos-centruose1
 
1.9%
https://www.tvmaze.com/episodes/1975746/friheden-2x06-afsnit-61
 
1.9%
https://www.tvmaze.com/episodes/2111708/world-wonder-ring-stardom-2020-12-20-stardom-osaka-dream-cinderella1
 
1.9%
https://www.tvmaze.com/episodes/1988623/redakcia-s03-special-redakcia-news-putin-i-otravlenie-kleveta-v-internete-raznotyk1
 
1.9%
https://www.tvmaze.com/episodes/1967013/bani-negri-pentru-zile-albe-1x05-barza1
 
1.9%
https://www.tvmaze.com/episodes/1985026/ultra-galaxy-fight-the-absolute-conspiracy-1x05-part-51
 
1.9%
https://www.tvmaze.com/episodes/1996817/pappas-pojkar-1x05-leo-blir-svartsjuk-pa-plugghastar1
 
1.9%
https://www.tvmaze.com/episodes/1997426/the-george-lucas-talk-show-s01-special-holiday-special1
 
1.9%
https://www.tvmaze.com/episodes/1997522/the-penalty-zone-1x15-episode-151
 
1.9%
Other values (44)44
81.5%

Length

2022-09-04T23:42:45.504978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2053350/ispoved-1x08-gnojnyj1
 
1.9%
https://www.tvmaze.com/episodes/2153870/der-ingen-skulle-tru-at-nokon-kunne-bu-19x04-lille-kalvoya1
 
1.9%
https://www.tvmaze.com/episodes/1985088/0-z-majklom-surom-5x16-peremozci-palanica-awards-2020-zelenskij-lesa-nikituk-vakarcuk-0-z-majklom-surom-161
 
1.9%
https://www.tvmaze.com/episodes/1988863/swallowed-star-1x05-episode-51
 
1.9%
https://www.tvmaze.com/episodes/2052510/wu-shen-zhu-zai-1x85-episode-851
 
1.9%
https://www.tvmaze.com/episodes/2012322/mans-diary-2x07-episode-71
 
1.9%
https://www.tvmaze.com/episodes/2071489/youths-in-the-breeze-1x19-full-time-sworn-enemy-031
 
1.9%
https://www.tvmaze.com/episodes/2071490/youths-in-the-breeze-1x20-full-time-sworn-enemy-041
 
1.9%
https://www.tvmaze.com/episodes/1956518/113-2x10-episode-101
 
1.9%
https://www.tvmaze.com/episodes/1977328/stjernestov-1x20-episode-201
 
1.9%
Other values (44)44
81.5%

Most occurring characters

ValueCountFrequency (%)
e396
 
8.7%
-370
 
8.1%
s275
 
6.0%
/270
 
5.9%
t264
 
5.8%
o228
 
5.0%
w187
 
4.1%
i182
 
4.0%
a170
 
3.7%
p162
 
3.5%
Other values (29)2060
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3125
68.5%
Decimal Number637
 
14.0%
Other Punctuation432
 
9.5%
Dash Punctuation370
 
8.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e396
12.7%
s275
 
8.8%
t264
 
8.4%
o228
 
7.3%
w187
 
6.0%
i182
 
5.8%
a170
 
5.4%
p162
 
5.2%
m149
 
4.8%
n133
 
4.3%
Other values (15)979
31.3%
Decimal Number
ValueCountFrequency (%)
1133
20.9%
2104
16.3%
098
15.4%
954
8.5%
548
 
7.5%
347
 
7.4%
643
 
6.8%
840
 
6.3%
737
 
5.8%
433
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/270
62.5%
.108
 
25.0%
:54
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-370
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3125
68.5%
Common1439
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e396
12.7%
s275
 
8.8%
t264
 
8.4%
o228
 
7.3%
w187
 
6.0%
i182
 
5.8%
a170
 
5.4%
p162
 
5.2%
m149
 
4.8%
n133
 
4.3%
Other values (15)979
31.3%
Common
ValueCountFrequency (%)
-370
25.7%
/270
18.8%
1133
 
9.2%
.108
 
7.5%
2104
 
7.2%
098
 
6.8%
954
 
3.8%
:54
 
3.8%
548
 
3.3%
347
 
3.3%
Other values (4)153
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e396
 
8.7%
-370
 
8.1%
s275
 
6.0%
/270
 
5.9%
t264
 
5.8%
o228
 
5.0%
w187
 
4.1%
i182
 
4.0%
a170
 
3.7%
p162
 
3.5%
Other values (29)2060
45.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
Гнойный
 
1
Sorošas ir kovidiotai prekybos centruose
 
1
Afsnit 6
 
1
Stardom Osaka Dream Cinderella
 
1
Редакция. News: Путин и отравление, клевета в интернете, «разнотык»
 
1
Other values (49)
49 

Length

Max length99
Median length65
Mean length19.18518519
Min length4

Characters and Unicode

Total characters1036
Distinct characters115
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st rowГнойный
2nd rowEpisode 11
3rd rowEpisode 5
4th rowEpisode 85
5th rowEpisode 7

Common Values

ValueCountFrequency (%)
Гнойный1
 
1.9%
Sorošas ir kovidiotai prekybos centruose1
 
1.9%
Afsnit 61
 
1.9%
Stardom Osaka Dream Cinderella1
 
1.9%
Редакция. News: Путин и отравление, клевета в интернете, «разнотык»1
 
1.9%
Barza1
 
1.9%
Part 51
 
1.9%
Leo blir svartsjuk på plugghästar1
 
1.9%
Holiday Special1
 
1.9%
Episode 151
 
1.9%
Other values (44)44
81.5%

Length

2022-09-04T23:42:45.600979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode14
 
8.0%
4
 
2.3%
folge4
 
2.3%
the4
 
2.3%
23
 
1.7%
43
 
1.7%
york2
 
1.1%
part2
 
1.1%
full-time2
 
1.1%
12
 
1.1%
Other values (128)135
77.1%

Most occurring characters

ValueCountFrequency (%)
122
 
11.8%
e75
 
7.2%
i55
 
5.3%
o49
 
4.7%
s48
 
4.6%
r40
 
3.9%
a39
 
3.8%
n34
 
3.3%
d32
 
3.1%
E25
 
2.4%
Other values (105)517
49.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter658
63.5%
Uppercase Letter154
 
14.9%
Space Separator122
 
11.8%
Decimal Number60
 
5.8%
Other Punctuation32
 
3.1%
Dash Punctuation5
 
0.5%
Currency Symbol2
 
0.2%
Close Punctuation1
 
0.1%
Initial Punctuation1
 
0.1%
Final Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e75
 
11.4%
i55
 
8.4%
o49
 
7.4%
s48
 
7.3%
r40
 
6.1%
a39
 
5.9%
n34
 
5.2%
d32
 
4.9%
p24
 
3.6%
l23
 
3.5%
Other values (45)239
36.3%
Uppercase Letter
ValueCountFrequency (%)
E25
16.2%
T15
 
9.7%
S11
 
7.1%
L10
 
6.5%
F9
 
5.8%
C8
 
5.2%
P7
 
4.5%
N7
 
4.5%
M7
 
4.5%
R6
 
3.9%
Other values (23)49
31.8%
Decimal Number
ValueCountFrequency (%)
216
26.7%
012
20.0%
110
16.7%
56
 
10.0%
65
 
8.3%
44
 
6.7%
73
 
5.0%
32
 
3.3%
81
 
1.7%
91
 
1.7%
Other Punctuation
ValueCountFrequency (%)
,9
28.1%
/5
15.6%
#5
15.6%
:5
15.6%
.2
 
6.2%
"2
 
6.2%
?1
 
3.1%
@1
 
3.1%
&1
 
3.1%
!1
 
3.1%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Initial Punctuation
ValueCountFrequency (%)
«1
100.0%
Final Punctuation
ValueCountFrequency (%)
»1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin697
67.3%
Common224
 
21.6%
Cyrillic115
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e75
 
10.8%
i55
 
7.9%
o49
 
7.0%
s48
 
6.9%
r40
 
5.7%
a39
 
5.6%
n34
 
4.9%
d32
 
4.6%
E25
 
3.6%
p24
 
3.4%
Other values (45)276
39.6%
Cyrillic
ValueCountFrequency (%)
е13
 
11.3%
к9
 
7.8%
н9
 
7.8%
а8
 
7.0%
и7
 
6.1%
т7
 
6.1%
р6
 
5.2%
о6
 
5.2%
л5
 
4.3%
й4
 
3.5%
Other values (23)41
35.7%
Common
ValueCountFrequency (%)
122
54.5%
216
 
7.1%
012
 
5.4%
110
 
4.5%
,9
 
4.0%
56
 
2.7%
/5
 
2.2%
-5
 
2.2%
#5
 
2.2%
:5
 
2.2%
Other values (17)29
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII910
87.8%
Cyrillic115
 
11.1%
None10
 
1.0%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
 
13.4%
e75
 
8.2%
i55
 
6.0%
o49
 
5.4%
s48
 
5.3%
r40
 
4.4%
a39
 
4.3%
n34
 
3.7%
d32
 
3.5%
E25
 
2.7%
Other values (62)391
43.0%
Cyrillic
ValueCountFrequency (%)
е13
 
11.3%
к9
 
7.8%
н9
 
7.8%
а8
 
7.0%
и7
 
6.1%
т7
 
6.1%
р6
 
5.2%
о6
 
5.2%
л5
 
4.3%
й4
 
3.5%
Other values (23)41
35.7%
None
ValueCountFrequency (%)
ø2
20.0%
Ø1
10.0%
æ1
10.0%
ä1
10.0%
š1
10.0%
«1
10.0%
»1
10.0%
å1
10.0%
é1
10.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191.3703704
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:45.678987image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)4

Descriptive statistics

Standard deviation589.6759998
Coefficient of variation (CV)3.081333848
Kurtosis6.603610172
Mean191.3703704
Median Absolute Deviation (MAD)0
Skewness2.89100347
Sum10334
Variance347717.7848
MonotonicityNot monotonic
2022-09-04T23:42:45.746982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
128
51.9%
27
 
13.0%
196
 
11.1%
20205
 
9.3%
33
 
5.6%
53
 
5.6%
61
 
1.9%
481
 
1.9%
ValueCountFrequency (%)
128
51.9%
27
 
13.0%
33
 
5.6%
53
 
5.6%
61
 
1.9%
196
 
11.1%
481
 
1.9%
20205
 
9.3%
ValueCountFrequency (%)
20205
 
9.3%
481
 
1.9%
196
 
11.1%
61
 
1.9%
53
 
5.6%
33
 
5.6%
27
 
13.0%
128
51.9%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)48.1%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.61538462
Minimum1
Maximum347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:45.824177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q14
median7.5
Q315.25
95-th percentile58.05
Maximum347
Range346
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation49.44402811
Coefficient of variation (CV)2.398404349
Kurtosis38.79187361
Mean20.61538462
Median Absolute Deviation (MAD)4
Skewness5.920699231
Sum1072
Variance2444.711916
MonotonicityNot monotonic
2022-09-04T23:42:45.903176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
56
 
11.1%
46
 
11.1%
104
 
7.4%
23
 
5.6%
73
 
5.6%
63
 
5.6%
13
 
5.6%
32
 
3.7%
162
 
3.7%
82
 
3.7%
Other values (15)18
33.3%
ValueCountFrequency (%)
13
5.6%
23
5.6%
32
 
3.7%
46
11.1%
56
11.1%
63
5.6%
73
5.6%
82
 
3.7%
91
 
1.9%
104
7.4%
ValueCountFrequency (%)
3471
1.9%
851
1.9%
631
1.9%
541
1.9%
521
1.9%
511
1.9%
481
1.9%
271
1.9%
202
3.7%
191
1.9%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
regular
52 
insignificant_special
 
1
significant_special
 
1

Length

Max length21
Median length7
Mean length7.481481481
Min length7

Characters and Unicode

Total characters404
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.7%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular52
96.3%
insignificant_special1
 
1.9%
significant_special1
 
1.9%

Length

2022-09-04T23:42:45.988177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:46.069969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular52
96.3%
insignificant_special1
 
1.9%
significant_special1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
r104
25.7%
a56
13.9%
e54
13.4%
g54
13.4%
l54
13.4%
u52
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (4)8
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter402
99.5%
Connector Punctuation2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r104
25.9%
a56
13.9%
e54
13.4%
g54
13.4%
l54
13.4%
u52
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (3)6
 
1.5%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin402
99.5%
Common2
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r104
25.9%
a56
13.9%
e54
13.4%
g54
13.4%
l54
13.4%
u52
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (3)6
 
1.5%
Common
ValueCountFrequency (%)
_2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r104
25.7%
a56
13.9%
e54
13.4%
g54
13.4%
l54
13.4%
u52
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (4)8
 
2.0%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size560.0 B
2020-12-20
54 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters540
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-20
2nd row2020-12-20
3rd row2020-12-20
4th row2020-12-20
5th row2020-12-20

Common Values

ValueCountFrequency (%)
2020-12-2054
100.0%

Length

2022-09-04T23:42:46.146165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:46.222093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2054
100.0%

Most occurring characters

ValueCountFrequency (%)
2216
40.0%
0162
30.0%
-108
20.0%
154
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number432
80.0%
Dash Punctuation108
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2216
50.0%
0162
37.5%
154
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2216
40.0%
0162
30.0%
-108
20.0%
154
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2216
40.0%
0162
30.0%
-108
20.0%
154
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size560.0 B
33 
10:00
20:00
06:00
 
2
12:00
 
1
Other values (10)
10 

Length

Max length5
Median length0
Mean length1.944444444
Min length0

Characters and Unicode

Total characters105
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)20.4%

Sample

1st row12:00
2nd row10:00
3rd row10:00
4th row10:00
5th row

Common Values

ValueCountFrequency (%)
33
61.1%
10:004
 
7.4%
20:004
 
7.4%
06:002
 
3.7%
12:001
 
1.9%
06:011
 
1.9%
06:021
 
1.9%
06:031
 
1.9%
06:041
 
1.9%
06:051
 
1.9%
Other values (5)5
 
9.3%

Length

2022-09-04T23:42:46.291514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:004
19.0%
20:004
19.0%
06:002
9.5%
12:001
 
4.8%
06:011
 
4.8%
06:021
 
4.8%
06:031
 
4.8%
06:041
 
4.8%
06:051
 
4.8%
06:061
 
4.8%
Other values (4)4
19.0%

Most occurring characters

ValueCountFrequency (%)
050
47.6%
:21
20.0%
19
 
8.6%
69
 
8.6%
28
 
7.6%
32
 
1.9%
42
 
1.9%
52
 
1.9%
71
 
1.0%
91
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number84
80.0%
Other Punctuation21
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
050
59.5%
19
 
10.7%
69
 
10.7%
28
 
9.5%
32
 
2.4%
42
 
2.4%
52
 
2.4%
71
 
1.2%
91
 
1.2%
Other Punctuation
ValueCountFrequency (%)
:21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
050
47.6%
:21
20.0%
19
 
8.6%
69
 
8.6%
28
 
7.6%
32
 
1.9%
42
 
1.9%
52
 
1.9%
71
 
1.0%
91
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
050
47.6%
:21
20.0%
19
 
8.6%
69
 
8.6%
28
 
7.6%
32
 
1.9%
42
 
1.9%
52
 
1.9%
71
 
1.0%
91
 
1.0%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size560.0 B
2020-12-20T12:00:00+00:00
20 
2020-12-20T11:00:00+00:00
2020-12-20T04:00:00+00:00
2020-12-20T17:00:00+00:00
2020-12-20T02:00:00+00:00
Other values (14)
16 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1350
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)22.2%

Sample

1st row2020-12-20T00:00:00+00:00
2nd row2020-12-20T02:00:00+00:00
3rd row2020-12-20T02:00:00+00:00
4th row2020-12-20T02:00:00+00:00
5th row2020-12-20T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-20T12:00:00+00:0020
37.0%
2020-12-20T11:00:00+00:009
16.7%
2020-12-20T04:00:00+00:003
 
5.6%
2020-12-20T17:00:00+00:003
 
5.6%
2020-12-20T02:00:00+00:003
 
5.6%
2020-12-21T01:00:00+00:002
 
3.7%
2020-12-20T05:00:00+00:002
 
3.7%
2020-12-21T00:00:00+00:001
 
1.9%
2020-12-20T21:35:00+00:001
 
1.9%
2020-12-20T15:00:00+00:001
 
1.9%
Other values (9)9
16.7%

Length

2022-09-04T23:42:46.367783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-20t12:00:00+00:0020
37.0%
2020-12-20t11:00:00+00:009
16.7%
2020-12-20t04:00:00+00:003
 
5.6%
2020-12-20t17:00:00+00:003
 
5.6%
2020-12-20t02:00:00+00:003
 
5.6%
2020-12-21t01:00:00+00:002
 
3.7%
2020-12-20t05:00:00+00:002
 
3.7%
2020-12-20t05:05:00+00:001
 
1.9%
2020-12-20t05:01:00+00:001
 
1.9%
2020-12-20t05:02:00+00:001
 
1.9%
Other values (9)9
16.7%

Most occurring characters

ValueCountFrequency (%)
0604
44.7%
2241
 
17.9%
:162
 
12.0%
-108
 
8.0%
1104
 
7.7%
T54
 
4.0%
+54
 
4.0%
511
 
0.8%
45
 
0.4%
73
 
0.2%
Other values (3)4
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number972
72.0%
Other Punctuation162
 
12.0%
Dash Punctuation108
 
8.0%
Uppercase Letter54
 
4.0%
Math Symbol54
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0604
62.1%
2241
 
24.8%
1104
 
10.7%
511
 
1.1%
45
 
0.5%
73
 
0.3%
32
 
0.2%
81
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:162
100.0%
Dash Punctuation
ValueCountFrequency (%)
-108
100.0%
Uppercase Letter
ValueCountFrequency (%)
T54
100.0%
Math Symbol
ValueCountFrequency (%)
+54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1296
96.0%
Latin54
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0604
46.6%
2241
 
18.6%
:162
 
12.5%
-108
 
8.3%
1104
 
8.0%
+54
 
4.2%
511
 
0.8%
45
 
0.4%
73
 
0.2%
32
 
0.2%
Other values (2)2
 
0.2%
Latin
ValueCountFrequency (%)
T54
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0604
44.7%
2241
 
17.9%
:162
 
12.0%
-108
 
8.0%
1104
 
7.7%
T54
 
4.0%
+54
 
4.0%
511
 
0.8%
45
 
0.4%
73
 
0.2%
Other values (3)4
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)51.0%
Missing5
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean44.36734694
Minimum4
Maximum196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:46.449844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7.4
Q122
median39
Q345
95-th percentile120
Maximum196
Range192
Interquartile range (IQR)23

Descriptive statistics

Standard deviation39.34446905
Coefficient of variation (CV)0.8867888609
Kurtosis6.46273864
Mean44.36734694
Median Absolute Deviation (MAD)10
Skewness2.433275924
Sum2174
Variance1547.987245
MonotonicityNot monotonic
2022-09-04T23:42:46.541381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
457
 
13.0%
394
 
7.4%
1203
 
5.6%
123
 
5.6%
442
 
3.7%
222
 
3.7%
342
 
3.7%
462
 
3.7%
152
 
3.7%
602
 
3.7%
Other values (15)20
37.0%
(Missing)5
 
9.3%
ValueCountFrequency (%)
41
 
1.9%
72
3.7%
81
 
1.9%
123
5.6%
152
3.7%
202
3.7%
211
 
1.9%
222
3.7%
231
 
1.9%
251
 
1.9%
ValueCountFrequency (%)
1961
 
1.9%
1801
 
1.9%
1203
5.6%
602
 
3.7%
511
 
1.9%
481
 
1.9%
462
 
3.7%
457
13.0%
442
 
3.7%
432
 
3.7%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing48
Missing (%)88.9%
Memory size560.0 B
<p>Father Vergara leaves for Rome to face his painful past. He requests a meeting with the Pope, but he discovers that Santoro is waiting for him too. Meanwhile in Pedraza, someone is about to return from the dead.</p>
<p>THE GEORGE LUCAS TALK SHOW HOLIDAY SPECIAL This holiday is yours, but we all share with you the hope that this day brings us closer to freedom, and to harmony, and to peace. No matter how different we appear, we're all the same in our struggle against the powers of evil and darkness. I hope that this day will always be a day of joy in which we can reconfirm our dedication and our courage. And more than anything else, our love for one another. This is the promise of the Tree of Life. Today, retired filmmaker GEORGE LUCAS (dead-eyed character actor CONNOR RATLIFF) and his talk show sidekick, WATTO (GRIFFIN NEWMAN, co-lead on AMAZON'S THE TICK) are raising money for FEEDING AMERICA. If you know anyone who might want to donate even as little as one dollar, please steer them towards this fundraiser today. They are joined, as always, by their snack-napping, nap-snacking producer PATRICK COTNOIR (aka PITY PAT aka THE GRIM SLEEPER aka STEAMBOOT LICKEY) whose druthers include you following him on twitter right now please: @patrickcotnoir Yippeeeee!. HAPPY LIFE DAY..</p>
<p>The Wistful Wish's journey comes to a close, but not before one last bit of terror from the deep.</p>
<p>There are few rules in the TikTok creator mansion other than cheaters get caught and canceled; lies and shady behavior are exposed when some of the members in the house discover a secret group chat.</p>
<p>Tamaki and Aya are finally reunited. Tamaki wants the two of them to live together, but Aya informs him that she wants to remain with her new father who has been taking care of her. A surprising figure appears before the dumbfounded group. When they learn of his ambition, IDOLiSH7's feelings are united--</p>

Length

Max length1080
Median length265
Mean length372.1666667
Min length104

Characters and Unicode

Total characters2233
Distinct characters68
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row<p>Father Vergara leaves for Rome to face his painful past. He requests a meeting with the Pope, but he discovers that Santoro is waiting for him too. Meanwhile in Pedraza, someone is about to return from the dead.</p>
2nd row<p>THE GEORGE LUCAS TALK SHOW HOLIDAY SPECIAL This holiday is yours, but we all share with you the hope that this day brings us closer to freedom, and to harmony, and to peace. No matter how different we appear, we're all the same in our struggle against the powers of evil and darkness. I hope that this day will always be a day of joy in which we can reconfirm our dedication and our courage. And more than anything else, our love for one another. This is the promise of the Tree of Life. Today, retired filmmaker GEORGE LUCAS (dead-eyed character actor CONNOR RATLIFF) and his talk show sidekick, WATTO (GRIFFIN NEWMAN, co-lead on AMAZON'S THE TICK) are raising money for FEEDING AMERICA. If you know anyone who might want to donate even as little as one dollar, please steer them towards this fundraiser today. They are joined, as always, by their snack-napping, nap-snacking producer PATRICK COTNOIR (aka PITY PAT aka THE GRIM SLEEPER aka STEAMBOOT LICKEY) whose druthers include you following him on twitter right now please: @patrickcotnoir Yippeeeee!. HAPPY LIFE DAY..</p>
3rd row<p>The Wistful Wish's journey comes to a close, but not before one last bit of terror from the deep.</p>
4th row<p>There are few rules in the TikTok creator mansion other than cheaters get caught and canceled; lies and shady behavior are exposed when some of the members in the house discover a secret group chat.</p>
5th row<p>Tamaki and Aya are finally reunited. Tamaki wants the two of them to live together, but Aya informs him that she wants to remain with her new father who has been taking care of her. A surprising figure appears before the dumbfounded group. When they learn of his ambition, IDOLiSH7's feelings are united--</p>

Common Values

ValueCountFrequency (%)
<p>Father Vergara leaves for Rome to face his painful past. He requests a meeting with the Pope, but he discovers that Santoro is waiting for him too. Meanwhile in Pedraza, someone is about to return from the dead.</p>1
 
1.9%
<p>THE GEORGE LUCAS TALK SHOW HOLIDAY SPECIAL This holiday is yours, but we all share with you the hope that this day brings us closer to freedom, and to harmony, and to peace. No matter how different we appear, we're all the same in our struggle against the powers of evil and darkness. I hope that this day will always be a day of joy in which we can reconfirm our dedication and our courage. And more than anything else, our love for one another. This is the promise of the Tree of Life. Today, retired filmmaker GEORGE LUCAS (dead-eyed character actor CONNOR RATLIFF) and his talk show sidekick, WATTO (GRIFFIN NEWMAN, co-lead on AMAZON'S THE TICK) are raising money for FEEDING AMERICA. If you know anyone who might want to donate even as little as one dollar, please steer them towards this fundraiser today. They are joined, as always, by their snack-napping, nap-snacking producer PATRICK COTNOIR (aka PITY PAT aka THE GRIM SLEEPER aka STEAMBOOT LICKEY) whose druthers include you following him on twitter right now please: @patrickcotnoir Yippeeeee!. HAPPY LIFE DAY..</p>1
 
1.9%
<p>The Wistful Wish's journey comes to a close, but not before one last bit of terror from the deep.</p>1
 
1.9%
<p>There are few rules in the TikTok creator mansion other than cheaters get caught and canceled; lies and shady behavior are exposed when some of the members in the house discover a secret group chat.</p>1
 
1.9%
<p>Tamaki and Aya are finally reunited. Tamaki wants the two of them to live together, but Aya informs him that she wants to remain with her new father who has been taking care of her. A surprising figure appears before the dumbfounded group. When they learn of his ambition, IDOLiSH7's feelings are united--</p>1
 
1.9%
<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>1
 
1.9%
(Missing)48
88.9%

Length

2022-09-04T23:42:46.618469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:46.724909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
the17
 
4.5%
to12
 
3.2%
of9
 
2.4%
and9
 
2.4%
a6
 
1.6%
are6
 
1.6%
this5
 
1.3%
in5
 
1.3%
his5
 
1.3%
that4
 
1.1%
Other values (234)299
79.3%

Most occurring characters

ValueCountFrequency (%)
371
16.6%
e202
 
9.0%
a138
 
6.2%
t130
 
5.8%
o124
 
5.6%
i109
 
4.9%
r105
 
4.7%
n100
 
4.5%
h96
 
4.3%
s88
 
3.9%
Other values (58)770
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1556
69.7%
Space Separator371
 
16.6%
Uppercase Letter210
 
9.4%
Other Punctuation57
 
2.6%
Math Symbol24
 
1.1%
Dash Punctuation6
 
0.3%
Open Punctuation3
 
0.1%
Close Punctuation3
 
0.1%
Decimal Number3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e202
13.0%
a138
 
8.9%
t130
 
8.4%
o124
 
8.0%
i109
 
7.0%
r105
 
6.7%
n100
 
6.4%
h96
 
6.2%
s88
 
5.7%
l55
 
3.5%
Other values (16)409
26.3%
Uppercase Letter
ValueCountFrequency (%)
T25
 
11.9%
A21
 
10.0%
E19
 
9.0%
I17
 
8.1%
O14
 
6.7%
R11
 
5.2%
L11
 
5.2%
C11
 
5.2%
P9
 
4.3%
H9
 
4.3%
Other values (13)63
30.0%
Other Punctuation
ValueCountFrequency (%)
,20
35.1%
.20
35.1%
/6
 
10.5%
'4
 
7.0%
"2
 
3.5%
!1
 
1.8%
;1
 
1.8%
@1
 
1.8%
:1
 
1.8%
?1
 
1.8%
Decimal Number
ValueCountFrequency (%)
51
33.3%
11
33.3%
71
33.3%
Math Symbol
ValueCountFrequency (%)
>12
50.0%
<12
50.0%
Space Separator
ValueCountFrequency (%)
371
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1766
79.1%
Common467
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e202
 
11.4%
a138
 
7.8%
t130
 
7.4%
o124
 
7.0%
i109
 
6.2%
r105
 
5.9%
n100
 
5.7%
h96
 
5.4%
s88
 
5.0%
l55
 
3.1%
Other values (39)619
35.1%
Common
ValueCountFrequency (%)
371
79.4%
,20
 
4.3%
.20
 
4.3%
>12
 
2.6%
<12
 
2.6%
-6
 
1.3%
/6
 
1.3%
'4
 
0.9%
(3
 
0.6%
)3
 
0.6%
Other values (9)10
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2233
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
16.6%
e202
 
9.0%
a138
 
6.2%
t130
 
5.8%
o124
 
5.6%
i109
 
4.9%
r105
 
4.7%
n100
 
4.5%
h96
 
4.3%
s88
 
3.9%
Other values (58)770
34.5%

rating.average
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing53
Missing (%)98.1%
Memory size560.0 B
8.8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row8.8

Common Values

ValueCountFrequency (%)
8.81
 
1.9%
(Missing)53
98.1%

Length

2022-09-04T23:42:46.963112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:47.036773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
8.81
100.0%

Most occurring characters

ValueCountFrequency (%)
82
66.7%
.1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2
66.7%
Other Punctuation1
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
82
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
82
66.7%
.1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
66.7%
.1
33.3%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
https://api.tvmaze.com/episodes/2053350
 
1
https://api.tvmaze.com/episodes/2005322
 
1
https://api.tvmaze.com/episodes/1975746
 
1
https://api.tvmaze.com/episodes/2111708
 
1
https://api.tvmaze.com/episodes/1988623
 
1
Other values (49)
49 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2106
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2053350
2nd rowhttps://api.tvmaze.com/episodes/1956340
3rd rowhttps://api.tvmaze.com/episodes/1988863
4th rowhttps://api.tvmaze.com/episodes/2052510
5th rowhttps://api.tvmaze.com/episodes/2012322

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20533501
 
1.9%
https://api.tvmaze.com/episodes/20053221
 
1.9%
https://api.tvmaze.com/episodes/19757461
 
1.9%
https://api.tvmaze.com/episodes/21117081
 
1.9%
https://api.tvmaze.com/episodes/19886231
 
1.9%
https://api.tvmaze.com/episodes/19670131
 
1.9%
https://api.tvmaze.com/episodes/19850261
 
1.9%
https://api.tvmaze.com/episodes/19968171
 
1.9%
https://api.tvmaze.com/episodes/19974261
 
1.9%
https://api.tvmaze.com/episodes/19975221
 
1.9%
Other values (44)44
81.5%

Length

2022-09-04T23:42:47.120948image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20533501
 
1.9%
https://api.tvmaze.com/episodes/21538701
 
1.9%
https://api.tvmaze.com/episodes/19850881
 
1.9%
https://api.tvmaze.com/episodes/19888631
 
1.9%
https://api.tvmaze.com/episodes/20525101
 
1.9%
https://api.tvmaze.com/episodes/20123221
 
1.9%
https://api.tvmaze.com/episodes/20714891
 
1.9%
https://api.tvmaze.com/episodes/20714901
 
1.9%
https://api.tvmaze.com/episodes/19565181
 
1.9%
https://api.tvmaze.com/episodes/19773281
 
1.9%
Other values (44)44
81.5%

Most occurring characters

ValueCountFrequency (%)
/216
 
10.3%
t162
 
7.7%
p162
 
7.7%
s162
 
7.7%
e162
 
7.7%
a108
 
5.1%
i108
 
5.1%
.108
 
5.1%
m108
 
5.1%
o108
 
5.1%
Other values (16)702
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1350
64.1%
Other Punctuation378
 
17.9%
Decimal Number378
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t162
12.0%
p162
12.0%
s162
12.0%
e162
12.0%
a108
8.0%
i108
8.0%
m108
8.0%
o108
8.0%
h54
 
4.0%
d54
 
4.0%
Other values (3)162
12.0%
Decimal Number
ValueCountFrequency (%)
165
17.2%
253
14.0%
946
12.2%
337
9.8%
835
9.3%
033
8.7%
631
8.2%
729
7.7%
528
7.4%
421
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/216
57.1%
.108
28.6%
:54
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1350
64.1%
Common756
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/216
28.6%
.108
14.3%
165
 
8.6%
:54
 
7.1%
253
 
7.0%
946
 
6.1%
337
 
4.9%
835
 
4.6%
033
 
4.4%
631
 
4.1%
Other values (3)78
 
10.3%
Latin
ValueCountFrequency (%)
t162
12.0%
p162
12.0%
s162
12.0%
e162
12.0%
a108
8.0%
i108
8.0%
m108
8.0%
o108
8.0%
h54
 
4.0%
d54
 
4.0%
Other values (3)162
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/216
 
10.3%
t162
 
7.7%
p162
 
7.7%
s162
 
7.7%
e162
 
7.7%
a108
 
5.1%
i108
 
5.1%
.108
 
5.1%
m108
 
5.1%
o108
 
5.1%
Other values (16)702
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45667.90741
Minimum2855
Maximum63155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:47.220978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2855
5-th percentile21443.65
Q137411.5
median50280
Q352838.75
95-th percentile63155
Maximum63155
Range60300
Interquartile range (IQR)15427.25

Descriptive statistics

Standard deviation13067.10851
Coefficient of variation (CV)0.2861332881
Kurtosis1.310122563
Mean45667.90741
Median Absolute Deviation (MAD)7487.5
Skewness-1.085091868
Sum2466067
Variance170749324.7
MonotonicityNot monotonic
2022-09-04T23:42:47.312978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
331726
 
11.1%
631554
 
7.4%
527432
 
3.7%
547622
 
3.7%
527812
 
3.7%
486831
 
1.9%
599511
 
1.9%
523031
 
1.9%
527371
 
1.9%
528581
 
1.9%
Other values (33)33
61.1%
ValueCountFrequency (%)
28551
 
1.9%
129061
 
1.9%
187521
 
1.9%
228931
 
1.9%
306061
 
1.9%
322141
 
1.9%
331726
11.1%
334631
 
1.9%
369071
 
1.9%
389251
 
1.9%
ValueCountFrequency (%)
631554
7.4%
617551
 
1.9%
599511
 
1.9%
593981
 
1.9%
583561
 
1.9%
578741
 
1.9%
558421
 
1.9%
547622
3.7%
540331
 
1.9%
528581
 
1.9%

_embedded.show.url
Categorical

HIGH CORRELATION

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
https://www.tvmaze.com/shows/33172/der-ingen-skulle-tru-at-nokon-kunne-bu
https://www.tvmaze.com/shows/63155/mord-in-der-familie-der-zauberwurfel
https://www.tvmaze.com/shows/52743/the-penalty-zone
 
2
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
 
2
https://www.tvmaze.com/shows/52781/love-script
 
2
Other values (38)
38 

Length

Max length77
Median length62
Mean length54.18518519
Min length38

Characters and Unicode

Total characters2926
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://www.tvmaze.com/shows/48683/ispoved
2nd rowhttps://www.tvmaze.com/shows/51471/hero-return
3rd rowhttps://www.tvmaze.com/shows/52178/swallowed-star
4th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai
5th rowhttps://www.tvmaze.com/shows/50398/mans-diary

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/33172/der-ingen-skulle-tru-at-nokon-kunne-bu6
 
11.1%
https://www.tvmaze.com/shows/63155/mord-in-der-familie-der-zauberwurfel4
 
7.4%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
3.7%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
3.7%
https://www.tvmaze.com/shows/52781/love-script2
 
3.7%
https://www.tvmaze.com/shows/48683/ispoved1
 
1.9%
https://www.tvmaze.com/shows/59951/awesomeness-tvs-next-influencer1
 
1.9%
https://www.tvmaze.com/shows/52303/pappas-pojkar1
 
1.9%
https://www.tvmaze.com/shows/52737/the-george-lucas-talk-show1
 
1.9%
https://www.tvmaze.com/shows/52858/laikykites-ten1
 
1.9%
Other values (33)33
61.1%

Length

2022-09-04T23:42:47.414210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/33172/der-ingen-skulle-tru-at-nokon-kunne-bu6
 
11.1%
https://www.tvmaze.com/shows/63155/mord-in-der-familie-der-zauberwurfel4
 
7.4%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
3.7%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
3.7%
https://www.tvmaze.com/shows/52781/love-script2
 
3.7%
https://www.tvmaze.com/shows/49524/30-monedas1
 
1.9%
https://www.tvmaze.com/shows/52178/swallowed-star1
 
1.9%
https://www.tvmaze.com/shows/54033/wu-shen-zhu-zai1
 
1.9%
https://www.tvmaze.com/shows/50398/mans-diary1
 
1.9%
https://www.tvmaze.com/shows/40240/1131
 
1.9%
Other values (33)33
61.1%

Most occurring characters

ValueCountFrequency (%)
/270
 
9.2%
w233
 
8.0%
t219
 
7.5%
s208
 
7.1%
e171
 
5.8%
o166
 
5.7%
h132
 
4.5%
m131
 
4.5%
-130
 
4.4%
a111
 
3.8%
Other values (29)1155
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2088
71.4%
Other Punctuation432
 
14.8%
Decimal Number276
 
9.4%
Dash Punctuation130
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w233
11.2%
t219
 
10.5%
s208
 
10.0%
e171
 
8.2%
o166
 
8.0%
h132
 
6.3%
m131
 
6.3%
a111
 
5.3%
n82
 
3.9%
r73
 
3.5%
Other values (15)562
26.9%
Decimal Number
ValueCountFrequency (%)
545
16.3%
343
15.6%
234
12.3%
129
10.5%
429
10.5%
725
9.1%
821
7.6%
618
 
6.5%
916
 
5.8%
016
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/270
62.5%
.108
 
25.0%
:54
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2088
71.4%
Common838
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w233
11.2%
t219
 
10.5%
s208
 
10.0%
e171
 
8.2%
o166
 
8.0%
h132
 
6.3%
m131
 
6.3%
a111
 
5.3%
n82
 
3.9%
r73
 
3.5%
Other values (15)562
26.9%
Common
ValueCountFrequency (%)
/270
32.2%
-130
15.5%
.108
 
12.9%
:54
 
6.4%
545
 
5.4%
343
 
5.1%
234
 
4.1%
129
 
3.5%
429
 
3.5%
725
 
3.0%
Other values (4)71
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/270
 
9.2%
w233
 
8.0%
t219
 
7.5%
s208
 
7.1%
e171
 
5.8%
o166
 
5.7%
h132
 
4.5%
m131
 
4.5%
-130
 
4.4%
a111
 
3.8%
Other values (29)1155
39.5%

_embedded.show.name
Categorical

HIGH CORRELATION

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
Der ingen skulle tru at nokon kunne bu
Mord in der Familie - Der Zauberwürfel
The Penalty Zone
 
2
Youths in the Breeze
 
2
Love Script
 
2
Other values (38)
38 

Length

Max length43
Median length28
Mean length19.62962963
Min length3

Characters and Unicode

Total characters1060
Distinct characters89
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowИсповедь
2nd rowHero Return
3rd rowSwallowed Star
4th rowWu Shen Zhu Zai
5th rowMan's Diary

Common Values

ValueCountFrequency (%)
Der ingen skulle tru at nokon kunne bu6
 
11.1%
Mord in der Familie - Der Zauberwürfel4
 
7.4%
The Penalty Zone2
 
3.7%
Youths in the Breeze2
 
3.7%
Love Script2
 
3.7%
Исповедь1
 
1.9%
Awesomeness TV's Next Influencer1
 
1.9%
Pappas pojkar1
 
1.9%
The George Lucas Talk Show1
 
1.9%
Laikykitės Ten1
 
1.9%
Other values (33)33
61.1%

Length

2022-09-04T23:42:47.506210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
der14
 
7.4%
the8
 
4.3%
skulle6
 
3.2%
tru6
 
3.2%
at6
 
3.2%
nokon6
 
3.2%
kunne6
 
3.2%
bu6
 
3.2%
ingen6
 
3.2%
in6
 
3.2%
Other values (98)118
62.8%

Most occurring characters

ValueCountFrequency (%)
134
 
12.6%
e112
 
10.6%
n79
 
7.5%
r67
 
6.3%
i52
 
4.9%
o49
 
4.6%
a48
 
4.5%
u47
 
4.4%
t46
 
4.3%
l39
 
3.7%
Other values (79)387
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter769
72.5%
Space Separator134
 
12.6%
Uppercase Letter132
 
12.5%
Other Punctuation9
 
0.8%
Decimal Number7
 
0.7%
Dash Punctuation4
 
0.4%
Close Punctuation2
 
0.2%
Currency Symbol2
 
0.2%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e112
14.6%
n79
 
10.3%
r67
 
8.7%
i52
 
6.8%
o49
 
6.4%
a48
 
6.2%
u47
 
6.1%
t46
 
6.0%
l39
 
5.1%
s32
 
4.2%
Other values (37)198
25.7%
Uppercase Letter
ValueCountFrequency (%)
D13
 
9.8%
S12
 
9.1%
T11
 
8.3%
M10
 
7.6%
Z8
 
6.1%
P8
 
6.1%
W7
 
5.3%
B7
 
5.3%
L7
 
5.3%
F7
 
5.3%
Other values (17)42
31.8%
Other Punctuation
ValueCountFrequency (%)
'5
55.6%
@1
 
11.1%
?1
 
11.1%
#1
 
11.1%
:1
 
11.1%
Decimal Number
ValueCountFrequency (%)
02
28.6%
12
28.6%
32
28.6%
71
14.3%
Currency Symbol
ValueCountFrequency (%)
1
50.0%
$1
50.0%
Space Separator
ValueCountFrequency (%)
134
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin872
82.3%
Common159
 
15.0%
Cyrillic29
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e112
 
12.8%
n79
 
9.1%
r67
 
7.7%
i52
 
6.0%
o49
 
5.6%
a48
 
5.5%
u47
 
5.4%
t46
 
5.3%
l39
 
4.5%
s32
 
3.7%
Other values (42)301
34.5%
Cyrillic
ValueCountFrequency (%)
о3
 
10.3%
а2
 
6.9%
к2
 
6.9%
д2
 
6.9%
е2
 
6.9%
м2
 
6.9%
р1
 
3.4%
у1
 
3.4%
й1
 
3.4%
Щ1
 
3.4%
Other values (12)12
41.4%
Common
ValueCountFrequency (%)
134
84.3%
'5
 
3.1%
-4
 
2.5%
02
 
1.3%
12
 
1.3%
32
 
1.3%
)2
 
1.3%
@1
 
0.6%
1
 
0.6%
?1
 
0.6%
Other values (5)5
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1022
96.4%
Cyrillic29
 
2.7%
None8
 
0.8%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
 
13.1%
e112
 
11.0%
n79
 
7.7%
r67
 
6.6%
i52
 
5.1%
o49
 
4.8%
a48
 
4.7%
u47
 
4.6%
t46
 
4.5%
l39
 
3.8%
Other values (52)349
34.1%
None
ValueCountFrequency (%)
ü4
50.0%
á2
25.0%
ø1
 
12.5%
ė1
 
12.5%
Cyrillic
ValueCountFrequency (%)
о3
 
10.3%
а2
 
6.9%
к2
 
6.9%
д2
 
6.9%
е2
 
6.9%
м2
 
6.9%
р1
 
3.4%
у1
 
3.4%
й1
 
3.4%
Щ1
 
3.4%
Other values (12)12
41.4%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size560.0 B
Scripted
23 
Documentary
10 
Animation
Talk Show
Reality
Other values (3)

Length

Max length11
Median length9
Mean length8.444444444
Min length4

Characters and Unicode

Total characters456
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDocumentary
2nd rowAnimation
3rd rowAnimation
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted23
42.6%
Documentary10
18.5%
Animation5
 
9.3%
Talk Show5
 
9.3%
Reality4
 
7.4%
Sports3
 
5.6%
Game Show2
 
3.7%
News2
 
3.7%

Length

2022-09-04T23:42:47.712210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:47.799546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted23
37.7%
documentary10
16.4%
show7
 
11.5%
animation5
 
8.2%
talk5
 
8.2%
reality4
 
6.6%
sports3
 
4.9%
game2
 
3.3%
news2
 
3.3%

Most occurring characters

ValueCountFrequency (%)
t45
 
9.9%
e41
 
9.0%
i37
 
8.1%
r36
 
7.9%
S33
 
7.2%
c33
 
7.2%
a26
 
5.7%
p26
 
5.7%
o25
 
5.5%
d23
 
5.0%
Other values (16)131
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter388
85.1%
Uppercase Letter61
 
13.4%
Space Separator7
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t45
11.6%
e41
10.6%
i37
9.5%
r36
9.3%
c33
8.5%
a26
 
6.7%
p26
 
6.7%
o25
 
6.4%
d23
 
5.9%
n20
 
5.2%
Other values (8)76
19.6%
Uppercase Letter
ValueCountFrequency (%)
S33
54.1%
D10
 
16.4%
T5
 
8.2%
A5
 
8.2%
R4
 
6.6%
G2
 
3.3%
N2
 
3.3%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin449
98.5%
Common7
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t45
 
10.0%
e41
 
9.1%
i37
 
8.2%
r36
 
8.0%
S33
 
7.3%
c33
 
7.3%
a26
 
5.8%
p26
 
5.8%
o25
 
5.6%
d23
 
5.1%
Other values (15)124
27.6%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t45
 
9.9%
e41
 
9.0%
i37
 
8.1%
r36
 
7.9%
S33
 
7.2%
c33
 
7.2%
a26
 
5.7%
p26
 
5.7%
o25
 
5.5%
d23
 
5.0%
Other values (16)131
28.7%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size560.0 B
Norwegian
12 
English
12 
Chinese
10 
German
Russian
Other values (10)
12 

Length

Max length10
Median length9.5
Mean length7.481481481
Min length6

Characters and Unicode

Total characters404
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)14.8%

Sample

1st rowRussian
2nd rowChinese
3rd rowChinese
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Norwegian12
22.2%
English12
22.2%
Chinese10
18.5%
German6
11.1%
Russian2
 
3.7%
Spanish2
 
3.7%
Japanese2
 
3.7%
Korean1
 
1.9%
Ukrainian1
 
1.9%
Danish1
 
1.9%
Other values (5)5
9.3%

Length

2022-09-04T23:42:47.890506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
norwegian12
22.2%
english12
22.2%
chinese10
18.5%
german6
11.1%
russian2
 
3.7%
spanish2
 
3.7%
japanese2
 
3.7%
korean1
 
1.9%
ukrainian1
 
1.9%
danish1
 
1.9%
Other values (5)5
9.3%

Most occurring characters

ValueCountFrequency (%)
n54
13.4%
e46
11.4%
i46
11.4%
a35
 
8.7%
s33
 
8.2%
h27
 
6.7%
g25
 
6.2%
r22
 
5.4%
o15
 
3.7%
w13
 
3.2%
Other values (22)88
21.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter350
86.6%
Uppercase Letter54
 
13.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n54
15.4%
e46
13.1%
i46
13.1%
a35
10.0%
s33
9.4%
h27
7.7%
g25
7.1%
r22
6.3%
o15
 
4.3%
w13
 
3.7%
Other values (9)34
9.7%
Uppercase Letter
ValueCountFrequency (%)
N12
22.2%
E12
22.2%
C10
18.5%
G6
11.1%
R3
 
5.6%
S3
 
5.6%
J2
 
3.7%
K1
 
1.9%
U1
 
1.9%
D1
 
1.9%
Other values (3)3
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Latin404
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n54
13.4%
e46
11.4%
i46
11.4%
a35
 
8.7%
s33
 
8.2%
h27
 
6.7%
g25
 
6.2%
r22
 
5.4%
o15
 
3.7%
w13
 
3.2%
Other values (22)88
21.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n54
13.4%
e46
11.4%
i46
11.4%
a35
 
8.7%
s33
 
8.2%
h27
 
6.7%
g25
 
6.2%
r22
 
5.4%
o15
 
3.7%
w13
 
3.2%
Other values (22)88
21.8%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size560.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
Running
33 
Ended
15 
To Be Determined

Length

Max length16
Median length7
Mean length7.444444444
Min length5

Characters and Unicode

Total characters402
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running33
61.1%
Ended15
27.8%
To Be Determined6
 
11.1%

Length

2022-09-04T23:42:47.972137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:48.047486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
running33
50.0%
ended15
22.7%
to6
 
9.1%
be6
 
9.1%
determined6
 
9.1%

Most occurring characters

ValueCountFrequency (%)
n120
29.9%
i39
 
9.7%
e39
 
9.7%
d36
 
9.0%
R33
 
8.2%
u33
 
8.2%
g33
 
8.2%
E15
 
3.7%
12
 
3.0%
T6
 
1.5%
Other values (6)36
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter324
80.6%
Uppercase Letter66
 
16.4%
Space Separator12
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n120
37.0%
i39
 
12.0%
e39
 
12.0%
d36
 
11.1%
u33
 
10.2%
g33
 
10.2%
o6
 
1.9%
t6
 
1.9%
r6
 
1.9%
m6
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
R33
50.0%
E15
22.7%
T6
 
9.1%
B6
 
9.1%
D6
 
9.1%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin390
97.0%
Common12
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n120
30.8%
i39
 
10.0%
e39
 
10.0%
d36
 
9.2%
R33
 
8.5%
u33
 
8.5%
g33
 
8.5%
E15
 
3.8%
T6
 
1.5%
o6
 
1.5%
Other values (5)30
 
7.7%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n120
29.9%
i39
 
9.7%
e39
 
9.7%
d36
 
9.0%
R33
 
8.2%
u33
 
8.2%
g33
 
8.2%
E15
 
3.7%
12
 
3.0%
T6
 
1.5%
Other values (6)36
 
9.0%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct14
Distinct (%)42.4%
Missing21
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean47.81818182
Minimum7
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:48.115181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7.6
Q120
median40
Q345
95-th percentile144
Maximum180
Range173
Interquartile range (IQR)25

Descriptive statistics

Standard deviation45.40612193
Coefficient of variation (CV)0.949557683
Kurtosis2.991279498
Mean47.81818182
Median Absolute Deviation (MAD)20
Skewness1.864622125
Sum1578
Variance2061.715909
MonotonicityNot monotonic
2022-09-04T23:42:48.187181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
457
 
13.0%
304
 
7.4%
123
 
5.6%
1203
 
5.6%
152
 
3.7%
72
 
3.7%
402
 
3.7%
202
 
3.7%
602
 
3.7%
1802
 
3.7%
Other values (4)4
 
7.4%
(Missing)21
38.9%
ValueCountFrequency (%)
72
 
3.7%
81
 
1.9%
123
5.6%
152
 
3.7%
202
 
3.7%
221
 
1.9%
251
 
1.9%
304
7.4%
402
 
3.7%
457
13.0%
ValueCountFrequency (%)
1802
 
3.7%
1203
5.6%
602
 
3.7%
481
 
1.9%
457
13.0%
402
 
3.7%
304
7.4%
251
 
1.9%
221
 
1.9%
202
 
3.7%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)54.0%
Missing4
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean44.98
Minimum5
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:48.270181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.45
Q120.25
median34
Q345
95-th percentile120
Maximum193
Range188
Interquartile range (IQR)24.75

Descriptive statistics

Standard deviation41.20059936
Coefficient of variation (CV)0.9159759751
Kurtosis5.15884244
Mean44.98
Median Absolute Deviation (MAD)12.5
Skewness2.226893916
Sum2249
Variance1697.489388
MonotonicityNot monotonic
2022-09-04T23:42:48.353315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4510
18.5%
346
 
11.1%
1204
 
7.4%
202
 
3.7%
292
 
3.7%
302
 
3.7%
472
 
3.7%
72
 
3.7%
122
 
3.7%
391
 
1.9%
Other values (17)17
31.5%
(Missing)4
 
7.4%
ValueCountFrequency (%)
51
1.9%
72
3.7%
81
1.9%
91
1.9%
111
1.9%
122
3.7%
151
1.9%
161
1.9%
181
1.9%
202
3.7%
ValueCountFrequency (%)
1931
 
1.9%
1881
 
1.9%
1204
 
7.4%
641
 
1.9%
601
 
1.9%
561
 
1.9%
472
 
3.7%
4510
18.5%
431
 
1.9%
391
 
1.9%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct37
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size560.0 B
2002-12-08
2020-12-20
2020-11-29
2020-11-22
 
3
2020-12-16
 
2
Other values (32)
33 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters540
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)57.4%

Sample

1st row2020-05-11
2nd row2020-10-18
3rd row2020-11-29
4th row2020-03-08
5th row2019-07-21

Common Values

ValueCountFrequency (%)
2002-12-086
 
11.1%
2020-12-206
 
11.1%
2020-11-294
 
7.4%
2020-11-223
 
5.6%
2020-12-162
 
3.7%
2020-12-132
 
3.7%
2020-05-111
 
1.9%
2019-09-011
 
1.9%
2020-05-041
 
1.9%
2016-09-111
 
1.9%
Other values (27)27
50.0%

Length

2022-09-04T23:42:48.436473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2002-12-086
 
11.1%
2020-12-206
 
11.1%
2020-11-294
 
7.4%
2020-11-223
 
5.6%
2020-12-162
 
3.7%
2020-12-132
 
3.7%
2020-11-081
 
1.9%
2020-10-181
 
1.9%
2017-09-181
 
1.9%
2015-06-031
 
1.9%
Other values (27)27
50.0%

Most occurring characters

ValueCountFrequency (%)
0139
25.7%
2130
24.1%
-108
20.0%
191
16.9%
919
 
3.5%
815
 
2.8%
610
 
1.9%
38
 
1.5%
58
 
1.5%
78
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number432
80.0%
Dash Punctuation108
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0139
32.2%
2130
30.1%
191
21.1%
919
 
4.4%
815
 
3.5%
610
 
2.3%
38
 
1.9%
58
 
1.9%
78
 
1.9%
44
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0139
25.7%
2130
24.1%
-108
20.0%
191
16.9%
919
 
3.5%
815
 
2.8%
610
 
1.9%
38
 
1.5%
58
 
1.5%
78
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0139
25.7%
2130
24.1%
-108
20.0%
191
16.9%
919
 
3.5%
815
 
2.8%
610
 
1.9%
38
 
1.5%
58
 
1.5%
78
 
1.5%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)53.3%
Missing39
Missing (%)72.2%
Memory size560.0 B
2020-12-20
2020-12-22
2021-01-09
2021-01-25
2022-08-30
Other values (3)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters150
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)26.7%

Sample

1st row2022-08-30
2nd row2020-12-22
3rd row2020-12-22
4th row2020-12-20
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2020-12-205
 
9.3%
2020-12-222
 
3.7%
2021-01-092
 
3.7%
2021-01-252
 
3.7%
2022-08-301
 
1.9%
2020-12-241
 
1.9%
2020-12-271
 
1.9%
2021-01-311
 
1.9%
(Missing)39
72.2%

Length

2022-09-04T23:42:48.510473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:48.597473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-205
33.3%
2020-12-222
 
13.3%
2021-01-092
 
13.3%
2021-01-252
 
13.3%
2022-08-301
 
6.7%
2020-12-241
 
6.7%
2020-12-271
 
6.7%
2021-01-311
 
6.7%

Most occurring characters

ValueCountFrequency (%)
253
35.3%
038
25.3%
-30
20.0%
120
 
13.3%
92
 
1.3%
52
 
1.3%
32
 
1.3%
81
 
0.7%
41
 
0.7%
71
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number120
80.0%
Dash Punctuation30
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
253
44.2%
038
31.7%
120
 
16.7%
92
 
1.7%
52
 
1.7%
32
 
1.7%
81
 
0.8%
41
 
0.8%
71
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
253
35.3%
038
25.3%
-30
20.0%
120
 
13.3%
92
 
1.3%
52
 
1.3%
32
 
1.3%
81
 
0.7%
41
 
0.7%
71
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
253
35.3%
038
25.3%
-30
20.0%
120
 
13.3%
92
 
1.3%
52
 
1.3%
32
 
1.3%
81
 
0.7%
41
 
0.7%
71
 
0.7%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct41
Distinct (%)80.4%
Missing3
Missing (%)5.6%
Memory size560.0 B
https://tv.nrk.no/serie/der-ingen-skulle-tru-at-nokon-kunne-bu
https://www.zdf.de/serien/mord-in-der-familie-der-zauberwuerfel
https://www.iqiyi.com/a_19rrhllpip.html
 
2
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef
 
2
https://shahid.mbc.net/en/series/Arous%20Beirut-season-1/season-376514-376515
 
1
Other values (36)
36 

Length

Max length105
Median length68
Mean length54.11764706
Min length21

Characters and Unicode

Total characters2760
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)72.5%

Sample

1st rowhttps://premier.one/collections/134
2nd rowhttps://v.qq.com/detail/q/q72jd29a3oxflsr.html
3rd rowhttps://v.qq.com/detail/3/324olz7ilvo2j5f.html
4th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html
5th rowhttps://www.bilibili.com/bangumi/media/md4314622

Common Values

ValueCountFrequency (%)
https://tv.nrk.no/serie/der-ingen-skulle-tru-at-nokon-kunne-bu6
 
11.1%
https://www.zdf.de/serien/mord-in-der-familie-der-zauberwuerfel4
 
7.4%
https://www.iqiyi.com/a_19rrhllpip.html2
 
3.7%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
3.7%
https://shahid.mbc.net/en/series/Arous%20Beirut-season-1/season-376514-3765151
 
1.9%
https://www.discoveryplus.se/program/pappas-pojkar1
 
1.9%
https://www.patrickcotnoir.com/glts1
 
1.9%
http://www.laisves.tv1
 
1.9%
https://www.amazon.com/Paranormal-Nightmare/dp/B07YLZPXT71
 
1.9%
https://motherlandsrpg.com1
 
1.9%
Other values (31)31
57.4%
(Missing)3
 
5.6%

Length

2022-09-04T23:42:48.697111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://tv.nrk.no/serie/der-ingen-skulle-tru-at-nokon-kunne-bu6
 
11.8%
https://www.zdf.de/serien/mord-in-der-familie-der-zauberwuerfel4
 
7.8%
https://www.iqiyi.com/a_19rrhllpip.html2
 
3.9%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
3.9%
https://es.hboespana.com/series/30-coins/37b0ccfe-0bf1-489e-b2a3-cae9f6307eb61
 
2.0%
https://v.qq.com/detail/3/324olz7ilvo2j5f.html1
 
2.0%
https://v.qq.com/detail/m/7q544xyrava3vxf.html1
 
2.0%
https://www.bilibili.com/bangumi/media/md43146221
 
2.0%
https://tv.nrk.no/serie/1131
 
2.0%
https://tv.nrk.no/serie/stjernestoev1
 
2.0%
Other values (31)31
60.8%

Most occurring characters

ValueCountFrequency (%)
/214
 
7.8%
e196
 
7.1%
t192
 
7.0%
s138
 
5.0%
n124
 
4.5%
r122
 
4.4%
o121
 
4.4%
i111
 
4.0%
.108
 
3.9%
-106
 
3.8%
Other values (59)1328
48.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1972
71.4%
Other Punctuation384
 
13.9%
Decimal Number188
 
6.8%
Dash Punctuation106
 
3.8%
Uppercase Letter88
 
3.2%
Math Symbol14
 
0.5%
Connector Punctuation8
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e196
 
9.9%
t192
 
9.7%
s138
 
7.0%
n124
 
6.3%
r122
 
6.2%
o121
 
6.1%
i111
 
5.6%
h97
 
4.9%
a96
 
4.9%
p91
 
4.6%
Other values (16)684
34.7%
Uppercase Letter
ValueCountFrequency (%)
N11
12.5%
T8
 
9.1%
P7
 
8.0%
U7
 
8.0%
W7
 
8.0%
M5
 
5.7%
D5
 
5.7%
L4
 
4.5%
B4
 
4.5%
X4
 
4.5%
Other values (14)26
29.5%
Decimal Number
ValueCountFrequency (%)
131
16.5%
328
14.9%
427
14.4%
224
12.8%
617
9.0%
017
9.0%
715
8.0%
512
 
6.4%
911
 
5.9%
86
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/214
55.7%
.108
28.1%
:51
 
13.3%
?5
 
1.3%
&5
 
1.3%
%1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-106
100.0%
Math Symbol
ValueCountFrequency (%)
=14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2060
74.6%
Common700
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e196
 
9.5%
t192
 
9.3%
s138
 
6.7%
n124
 
6.0%
r122
 
5.9%
o121
 
5.9%
i111
 
5.4%
h97
 
4.7%
a96
 
4.7%
p91
 
4.4%
Other values (40)772
37.5%
Common
ValueCountFrequency (%)
/214
30.6%
.108
15.4%
-106
15.1%
:51
 
7.3%
131
 
4.4%
328
 
4.0%
427
 
3.9%
224
 
3.4%
617
 
2.4%
017
 
2.4%
Other values (9)77
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/214
 
7.8%
e196
 
7.1%
t192
 
7.0%
s138
 
5.0%
n124
 
4.5%
r122
 
4.4%
o121
 
4.4%
i111
 
4.0%
.108
 
3.9%
-106
 
3.8%
Other values (59)1328
48.1%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size560.0 B
38 
20:00
10:00
12:00
 
1
20:20
 
1
Other values (5)

Length

Max length5
Median length0
Mean length1.481481481
Min length0

Characters and Unicode

Total characters80
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)13.0%

Sample

1st row12:00
2nd row10:00
3rd row10:00
4th row10:00
5th row

Common Values

ValueCountFrequency (%)
38
70.4%
20:005
 
9.3%
10:004
 
7.4%
12:001
 
1.9%
20:201
 
1.9%
06:001
 
1.9%
17:001
 
1.9%
14:001
 
1.9%
22:301
 
1.9%
22:151
 
1.9%

Length

2022-09-04T23:42:48.783112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:48.869112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
20:005
31.2%
10:004
25.0%
12:001
 
6.2%
20:201
 
6.2%
06:001
 
6.2%
17:001
 
6.2%
14:001
 
6.2%
22:301
 
6.2%
22:151
 
6.2%

Most occurring characters

ValueCountFrequency (%)
039
48.8%
:16
20.0%
212
 
15.0%
18
 
10.0%
61
 
1.2%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number64
80.0%
Other Punctuation16
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
039
60.9%
212
 
18.8%
18
 
12.5%
61
 
1.6%
71
 
1.6%
41
 
1.6%
31
 
1.6%
51
 
1.6%
Other Punctuation
ValueCountFrequency (%)
:16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
039
48.8%
:16
20.0%
212
 
15.0%
18
 
10.0%
61
 
1.2%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
039
48.8%
:16
20.0%
212
 
15.0%
18
 
10.0%
61
 
1.2%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size560.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing50
Missing (%)92.6%
Memory size560.0 B
7.7
8.1
8.2
7.8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters12
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row7.7
2nd row8.1
3rd row8.2
4th row7.8

Common Values

ValueCountFrequency (%)
7.71
 
1.9%
8.11
 
1.9%
8.21
 
1.9%
7.81
 
1.9%
(Missing)50
92.6%

Length

2022-09-04T23:42:48.954111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:49.035111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
7.71
25.0%
8.11
25.0%
8.21
25.0%
7.81
25.0%

Most occurring characters

ValueCountFrequency (%)
.4
33.3%
73
25.0%
83
25.0%
11
 
8.3%
21
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number8
66.7%
Other Punctuation4
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
73
37.5%
83
37.5%
11
 
12.5%
21
 
12.5%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.4
33.3%
73
25.0%
83
25.0%
11
 
8.3%
21
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.4
33.3%
73
25.0%
83
25.0%
11
 
8.3%
21
 
8.3%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct31
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.22222222
Minimum0
Maximum95
Zeros4
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:49.112111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median34
Q351
95-th percentile83.75
Maximum95
Range95
Interquartile range (IQR)31

Descriptive statistics

Standard deviation25.66082593
Coefficient of variation (CV)0.6893953235
Kurtosis-0.3855353654
Mean37.22222222
Median Absolute Deviation (MAD)17
Skewness0.5226843923
Sum2010
Variance658.4779874
MonotonicityNot monotonic
2022-09-04T23:42:49.195282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
517
 
13.0%
205
 
9.3%
04
 
7.4%
273
 
5.6%
42
 
3.7%
32
 
3.7%
442
 
3.7%
332
 
3.7%
352
 
3.7%
602
 
3.7%
Other values (21)23
42.6%
ValueCountFrequency (%)
04
7.4%
32
 
3.7%
42
 
3.7%
121
 
1.9%
151
 
1.9%
161
 
1.9%
171
 
1.9%
205
9.3%
221
 
1.9%
241
 
1.9%
ValueCountFrequency (%)
951
 
1.9%
931
 
1.9%
871
 
1.9%
822
 
3.7%
792
 
3.7%
671
 
1.9%
602
 
3.7%
561
 
1.9%
517
13.0%
501
 
1.9%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)53.8%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean189.1538462
Minimum3
Maximum443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:49.278709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile21
Q163
median232
Q3308.25
95-th percentile363.25
Maximum443
Range440
Interquartile range (IQR)245.25

Descriptive statistics

Standard deviation129.7643996
Coefficient of variation (CV)0.6860256993
Kurtosis-1.392252347
Mean189.1538462
Median Absolute Deviation (MAD)120
Skewness0.02102808692
Sum9836
Variance16838.7994
MonotonicityNot monotonic
2022-09-04T23:42:49.355710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2389
16.7%
217
 
13.0%
3524
 
7.4%
3273
 
5.6%
1043
 
5.6%
2262
 
3.7%
1182
 
3.7%
672
 
3.7%
151
 
1.9%
3791
 
1.9%
Other values (18)18
33.3%
(Missing)2
 
3.7%
ValueCountFrequency (%)
31
 
1.9%
151
 
1.9%
217
13.0%
221
 
1.9%
321
 
1.9%
451
 
1.9%
511
 
1.9%
672
 
3.7%
1031
 
1.9%
1043
5.6%
ValueCountFrequency (%)
4431
 
1.9%
3791
 
1.9%
3771
 
1.9%
3524
7.4%
3471
 
1.9%
3311
 
1.9%
3273
5.6%
3211
 
1.9%
3041
 
1.9%
2941
 
1.9%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)53.8%
Missing2
Missing (%)3.7%
Memory size560.0 B
NRK TV
YouTube
ZDFmediathek
TV 2 Play
Tencent QQ
Other values (23)
26 

Length

Max length19
Median length13
Mean length8.211538462
Min length4

Characters and Unicode

Total characters427
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)38.5%

Sample

1st rowPremier
2nd rowTencent QQ
3rd rowTencent QQ
4th rowTencent QQ
5th rowBilibili

Common Values

ValueCountFrequency (%)
NRK TV9
16.7%
YouTube7
 
13.0%
ZDFmediathek4
 
7.4%
TV 2 Play3
 
5.6%
Tencent QQ3
 
5.6%
Mango TV2
 
3.7%
Youku2
 
3.7%
iQIYI2
 
3.7%
WWE Network1
 
1.9%
Shahid1
 
1.9%
Other values (18)18
33.3%
(Missing)2
 
3.7%

Length

2022-09-04T23:42:49.442709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv15
18.8%
nrk9
 
11.2%
youtube7
 
8.8%
zdfmediathek4
 
5.0%
23
 
3.8%
play3
 
3.8%
tencent3
 
3.8%
qq3
 
3.8%
mango2
 
2.5%
youku2
 
2.5%
Other values (28)29
36.2%

Most occurring characters

ValueCountFrequency (%)
e34
 
8.0%
28
 
6.6%
T27
 
6.3%
o24
 
5.6%
a22
 
5.2%
u21
 
4.9%
i18
 
4.2%
V17
 
4.0%
t16
 
3.7%
R12
 
2.8%
Other values (37)208
48.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter241
56.4%
Uppercase Letter152
35.6%
Space Separator28
 
6.6%
Math Symbol3
 
0.7%
Decimal Number3
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T27
17.8%
V17
11.2%
R12
 
7.9%
N11
 
7.2%
P11
 
7.2%
Y11
 
7.2%
K10
 
6.6%
Q8
 
5.3%
F6
 
3.9%
I5
 
3.3%
Other values (13)34
22.4%
Lowercase Letter
ValueCountFrequency (%)
e34
14.1%
o24
 
10.0%
a22
 
9.1%
u21
 
8.7%
i18
 
7.5%
t16
 
6.6%
l11
 
4.6%
r10
 
4.1%
n10
 
4.1%
d9
 
3.7%
Other values (11)66
27.4%
Space Separator
ValueCountFrequency (%)
28
100.0%
Math Symbol
ValueCountFrequency (%)
+3
100.0%
Decimal Number
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin393
92.0%
Common34
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e34
 
8.7%
T27
 
6.9%
o24
 
6.1%
a22
 
5.6%
u21
 
5.3%
i18
 
4.6%
V17
 
4.3%
t16
 
4.1%
R12
 
3.1%
N11
 
2.8%
Other values (34)191
48.6%
Common
ValueCountFrequency (%)
28
82.4%
+3
 
8.8%
23
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII427
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e34
 
8.0%
28
 
6.6%
T27
 
6.3%
o24
 
5.6%
a22
 
5.2%
u21
 
4.9%
i18
 
4.2%
V17
 
4.0%
t16
 
3.7%
R12
 
2.8%
Other values (37)208
48.7%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)23.5%
Missing20
Missing (%)37.0%
Memory size560.0 B
Norway
12 
China
United States
Germany
Russian Federation
 
1
Other values (3)

Length

Max length18
Median length13
Mean length7.794117647
Min length5

Characters and Unicode

Total characters265
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st rowRussian Federation
2nd rowChina
3rd rowChina
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
Norway12
22.2%
China8
 
14.8%
United States6
 
11.1%
Germany4
 
7.4%
Russian Federation1
 
1.9%
Korea, Republic of1
 
1.9%
Spain1
 
1.9%
Brazil1
 
1.9%
(Missing)20
37.0%

Length

2022-09-04T23:42:49.525710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:49.614710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
norway12
27.9%
china8
18.6%
united6
14.0%
states6
14.0%
germany4
 
9.3%
russian1
 
2.3%
federation1
 
2.3%
korea1
 
2.3%
republic1
 
2.3%
of1
 
2.3%
Other values (2)2
 
4.7%

Most occurring characters

ValueCountFrequency (%)
a35
13.2%
n21
 
7.9%
e20
 
7.5%
r19
 
7.2%
i19
 
7.2%
t19
 
7.2%
y16
 
6.0%
o15
 
5.7%
N12
 
4.5%
w12
 
4.5%
Other values (21)77
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter213
80.4%
Uppercase Letter42
 
15.8%
Space Separator9
 
3.4%
Other Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a35
16.4%
n21
9.9%
e20
9.4%
r19
8.9%
i19
8.9%
t19
8.9%
y16
7.5%
o15
7.0%
w12
 
5.6%
h8
 
3.8%
Other values (10)29
13.6%
Uppercase Letter
ValueCountFrequency (%)
N12
28.6%
C8
19.0%
S7
16.7%
U6
14.3%
G4
 
9.5%
R2
 
4.8%
F1
 
2.4%
K1
 
2.4%
B1
 
2.4%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin255
96.2%
Common10
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a35
13.7%
n21
 
8.2%
e20
 
7.8%
r19
 
7.5%
i19
 
7.5%
t19
 
7.5%
y16
 
6.3%
o15
 
5.9%
N12
 
4.7%
w12
 
4.7%
Other values (19)67
26.3%
Common
ValueCountFrequency (%)
9
90.0%
,1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a35
13.2%
n21
 
7.9%
e20
 
7.5%
r19
 
7.2%
i19
 
7.2%
t19
 
7.2%
y16
 
6.0%
o15
 
5.7%
N12
 
4.5%
w12
 
4.5%
Other values (21)77
29.1%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)23.5%
Missing20
Missing (%)37.0%
Memory size560.0 B
NO
12 
CN
US
DE
RU
 
1
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters68
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st rowRU
2nd rowCN
3rd rowCN
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
NO12
22.2%
CN8
 
14.8%
US6
 
11.1%
DE4
 
7.4%
RU1
 
1.9%
KR1
 
1.9%
ES1
 
1.9%
BR1
 
1.9%
(Missing)20
37.0%

Length

2022-09-04T23:42:49.821031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:49.905150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
no12
35.3%
cn8
23.5%
us6
17.6%
de4
 
11.8%
ru1
 
2.9%
kr1
 
2.9%
es1
 
2.9%
br1
 
2.9%

Most occurring characters

ValueCountFrequency (%)
N20
29.4%
O12
17.6%
C8
 
11.8%
U7
 
10.3%
S7
 
10.3%
E5
 
7.4%
D4
 
5.9%
R3
 
4.4%
K1
 
1.5%
B1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter68
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N20
29.4%
O12
17.6%
C8
 
11.8%
U7
 
10.3%
S7
 
10.3%
E5
 
7.4%
D4
 
5.9%
R3
 
4.4%
K1
 
1.5%
B1
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Latin68
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N20
29.4%
O12
17.6%
C8
 
11.8%
U7
 
10.3%
S7
 
10.3%
E5
 
7.4%
D4
 
5.9%
R3
 
4.4%
K1
 
1.5%
B1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII68
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N20
29.4%
O12
17.6%
C8
 
11.8%
U7
 
10.3%
S7
 
10.3%
E5
 
7.4%
D4
 
5.9%
R3
 
4.4%
K1
 
1.5%
B1
 
1.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)23.5%
Missing20
Missing (%)37.0%
Memory size560.0 B
Europe/Oslo
12 
Asia/Shanghai
America/New_York
Europe/Busingen
Asia/Kamchatka
 
1
Other values (3)

Length

Max length16
Median length15
Mean length13.05882353
Min length10

Characters and Unicode

Total characters444
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Europe/Oslo12
22.2%
Asia/Shanghai8
 
14.8%
America/New_York6
 
11.1%
Europe/Busingen4
 
7.4%
Asia/Kamchatka1
 
1.9%
Asia/Seoul1
 
1.9%
Europe/Madrid1
 
1.9%
America/Noronha1
 
1.9%
(Missing)20
37.0%

Length

2022-09-04T23:42:49.991150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:50.082279image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/oslo12
35.3%
asia/shanghai8
23.5%
america/new_york6
17.6%
europe/busingen4
 
11.8%
asia/kamchatka1
 
2.9%
asia/seoul1
 
2.9%
europe/madrid1
 
2.9%
america/noronha1
 
2.9%

Most occurring characters

ValueCountFrequency (%)
o38
 
8.6%
a38
 
8.6%
e35
 
7.9%
/34
 
7.7%
r32
 
7.2%
i30
 
6.8%
s26
 
5.9%
u22
 
5.0%
h18
 
4.1%
n17
 
3.8%
Other values (19)154
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter330
74.3%
Uppercase Letter74
 
16.7%
Other Punctuation34
 
7.7%
Connector Punctuation6
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o38
11.5%
a38
11.5%
e35
10.6%
r32
9.7%
i30
9.1%
s26
7.9%
u22
 
6.7%
h18
 
5.5%
n17
 
5.2%
p17
 
5.2%
Other values (8)57
17.3%
Uppercase Letter
ValueCountFrequency (%)
E17
23.0%
A17
23.0%
O12
16.2%
S9
12.2%
N7
9.5%
Y6
 
8.1%
B4
 
5.4%
K1
 
1.4%
M1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/34
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin404
91.0%
Common40
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o38
 
9.4%
a38
 
9.4%
e35
 
8.7%
r32
 
7.9%
i30
 
7.4%
s26
 
6.4%
u22
 
5.4%
h18
 
4.5%
n17
 
4.2%
E17
 
4.2%
Other values (17)131
32.4%
Common
ValueCountFrequency (%)
/34
85.0%
_6
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o38
 
8.6%
a38
 
8.6%
e35
 
7.9%
/34
 
7.7%
r32
 
7.2%
i30
 
6.8%
s26
 
5.9%
u22
 
5.0%
h18
 
4.1%
n17
 
3.8%
Other values (19)154
34.7%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)50.0%
Missing34
Missing (%)63.0%
Memory size560.0 B
https://www.youtube.com
https://v.qq.com/
https://www.iq.com/
https://w.mgtv.com/
https://tv.kakao.com/top
Other values (5)

Length

Max length30
Median length26
Mean length22.15
Min length17

Characters and Unicode

Total characters443
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)30.0%

Sample

1st rowhttps://v.qq.com/
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.kakao.com/top
5th rowhttps://www.youtube.com

Common Values

ValueCountFrequency (%)
https://www.youtube.com7
 
13.0%
https://v.qq.com/3
 
5.6%
https://www.iq.com/2
 
3.7%
https://w.mgtv.com/2
 
3.7%
https://tv.kakao.com/top1
 
1.9%
https://viaplay.com1
 
1.9%
https://www.discoveryplus.com/1
 
1.9%
https://www.primevideo.com1
 
1.9%
https://www.paramountplus.com/1
 
1.9%
https://www.peacocktv.com/1
 
1.9%
(Missing)34
63.0%

Length

2022-09-04T23:42:50.192068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:50.296176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com7
35.0%
https://v.qq.com3
15.0%
https://www.iq.com2
 
10.0%
https://w.mgtv.com2
 
10.0%
https://tv.kakao.com/top1
 
5.0%
https://viaplay.com1
 
5.0%
https://www.discoveryplus.com1
 
5.0%
https://www.primevideo.com1
 
5.0%
https://www.paramountplus.com1
 
5.0%
https://www.peacocktv.com1
 
5.0%

Most occurring characters

ValueCountFrequency (%)
t53
12.0%
/51
11.5%
w41
 
9.3%
.39
 
8.8%
o33
 
7.4%
p27
 
6.1%
m24
 
5.4%
s23
 
5.2%
c23
 
5.2%
h20
 
4.5%
Other values (15)109
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter333
75.2%
Other Punctuation110
 
24.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t53
15.9%
w41
12.3%
o33
9.9%
p27
8.1%
m24
 
7.2%
s23
 
6.9%
c23
 
6.9%
h20
 
6.0%
u17
 
5.1%
e11
 
3.3%
Other values (12)61
18.3%
Other Punctuation
ValueCountFrequency (%)
/51
46.4%
.39
35.5%
:20
 
18.2%

Most occurring scripts

ValueCountFrequency (%)
Latin333
75.2%
Common110
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t53
15.9%
w41
12.3%
o33
9.9%
p27
8.1%
m24
 
7.2%
s23
 
6.9%
c23
 
6.9%
h20
 
6.0%
u17
 
5.1%
e11
 
3.3%
Other values (12)61
18.3%
Common
ValueCountFrequency (%)
/51
46.4%
.39
35.5%
:20
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t53
12.0%
/51
11.5%
w41
 
9.3%
.39
 
8.8%
o33
 
7.4%
p27
 
6.1%
m24
 
5.4%
s23
 
5.2%
c23
 
5.2%
h20
 
4.5%
Other values (15)109
24.6%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.externals.tvrage
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct31
Distinct (%)75.6%
Missing13
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean328392.8049
Minimum85436
Maximum413627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:50.407182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum85436
5-th percentile85436
Q1310336
median371044
Q3392598
95-th percentile413627
Maximum413627
Range328191
Interquartile range (IQR)82262

Descriptive statistics

Standard deviation107735.5201
Coefficient of variation (CV)0.328069064
Kurtosis1.375213099
Mean328392.8049
Median Absolute Deviation (MAD)22682
Skewness-1.675937651
Sum13464105
Variance1.160694229 × 1010
MonotonicityNot monotonic
2022-09-04T23:42:50.492186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
854366
 
11.1%
4136274
 
7.4%
3937262
 
3.7%
3972472
 
3.7%
3697981
 
1.9%
3936971
 
1.9%
3386311
 
1.9%
3839641
 
1.9%
3710441
 
1.9%
2776911
 
1.9%
Other values (21)21
38.9%
(Missing)13
24.1%
ValueCountFrequency (%)
854366
11.1%
2651931
 
1.9%
2776911
 
1.9%
2941791
 
1.9%
3101021
 
1.9%
3103361
 
1.9%
3373361
 
1.9%
3386311
 
1.9%
3544581
 
1.9%
3575371
 
1.9%
ValueCountFrequency (%)
4136274
7.4%
3972472
3.7%
3937262
3.7%
3936971
 
1.9%
3926491
 
1.9%
3925981
 
1.9%
3919761
 
1.9%
3905861
 
1.9%
3904711
 
1.9%
3901301
 
1.9%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct21
Distinct (%)77.8%
Missing27
Missing (%)50.0%
Memory size560.0 B
tt5810780
tt13599000
tt13010912
 
1
tt10241812
 
1
tt6468694
 
1
Other values (16)
16 

Length

Max length10
Median length10
Mean length9.518518519
Min length9

Characters and Unicode

Total characters257
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)70.4%

Sample

1st rowtt13005000
2nd rowtt11492320
3rd rowtt5810780
4th rowtt5810780
5th rowtt5810780

Common Values

ValueCountFrequency (%)
tt58107806
 
11.1%
tt135990002
 
3.7%
tt130109121
 
1.9%
tt102418121
 
1.9%
tt64686941
 
1.9%
tt03817531
 
1.9%
tt124579461
 
1.9%
tt132104701
 
1.9%
tt60942681
 
1.9%
tt126613101
 
1.9%
Other values (11)11
20.4%
(Missing)27
50.0%

Length

2022-09-04T23:42:50.583188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt58107806
22.2%
tt135990002
 
7.4%
tt130050001
 
3.7%
tt114923201
 
3.7%
tt69407301
 
3.7%
tt107270441
 
3.7%
tt97643861
 
3.7%
tt54238601
 
3.7%
tt116772861
 
3.7%
tt76948741
 
3.7%
Other values (11)11
40.7%

Most occurring characters

ValueCountFrequency (%)
t54
21.0%
042
16.3%
131
12.1%
821
 
8.2%
718
 
7.0%
318
 
7.0%
417
 
6.6%
617
 
6.6%
915
 
5.8%
512
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number203
79.0%
Lowercase Letter54
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
042
20.7%
131
15.3%
821
10.3%
718
8.9%
318
8.9%
417
8.4%
617
8.4%
915
 
7.4%
512
 
5.9%
212
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
t54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common203
79.0%
Latin54
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
042
20.7%
131
15.3%
821
10.3%
718
8.9%
318
8.9%
417
8.4%
617
8.4%
915
 
7.4%
512
 
5.9%
212
 
5.9%
Latin
ValueCountFrequency (%)
t54
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t54
21.0%
042
16.3%
131
12.1%
821
 
8.2%
718
 
7.0%
318
 
7.0%
417
 
6.6%
617
 
6.6%
915
 
5.8%
512
 
4.7%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING

Distinct40
Distinct (%)78.4%
Missing3
Missing (%)5.6%
Memory size560.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/381/954567.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/416/1040572.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/291/729461.jpg
 
2
Other values (35)
35 

Length

Max length72
Median length71
Mean length71.17647059
Min length70

Characters and Unicode

Total characters3630
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)68.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713049.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/381/954567.jpg6
 
11.1%
https://static.tvmaze.com/uploads/images/medium_portrait/416/1040572.jpg4
 
7.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729461.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713049.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/389/973148.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718562.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729040.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/408/1021576.jpg1
 
1.9%
Other values (30)30
55.6%
(Missing)3
 
5.6%

Length

2022-09-04T23:42:50.672429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/381/954567.jpg6
 
11.8%
https://static.tvmaze.com/uploads/images/medium_portrait/416/1040572.jpg4
 
7.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729461.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/medium_portrait/412/1031049.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/287/717764.jpg1
 
2.0%
Other values (30)30
58.8%

Most occurring characters

ValueCountFrequency (%)
/357
 
9.8%
t357
 
9.8%
a255
 
7.0%
m255
 
7.0%
p204
 
5.6%
s204
 
5.6%
i204
 
5.6%
.153
 
4.2%
e153
 
4.2%
o153
 
4.2%
Other values (22)1335
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2550
70.2%
Other Punctuation561
 
15.5%
Decimal Number468
 
12.9%
Connector Punctuation51
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t357
14.0%
a255
10.0%
m255
10.0%
p204
 
8.0%
s204
 
8.0%
i204
 
8.0%
e153
 
6.0%
o153
 
6.0%
d102
 
4.0%
u102
 
4.0%
Other values (8)561
22.0%
Decimal Number
ValueCountFrequency (%)
173
15.6%
758
12.4%
250
10.7%
449
10.5%
945
9.6%
843
9.2%
043
9.2%
542
9.0%
634
7.3%
331
6.6%
Other Punctuation
ValueCountFrequency (%)
/357
63.6%
.153
27.3%
:51
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2550
70.2%
Common1080
29.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t357
14.0%
a255
10.0%
m255
10.0%
p204
 
8.0%
s204
 
8.0%
i204
 
8.0%
e153
 
6.0%
o153
 
6.0%
d102
 
4.0%
u102
 
4.0%
Other values (8)561
22.0%
Common
ValueCountFrequency (%)
/357
33.1%
.153
14.2%
173
 
6.8%
758
 
5.4%
_51
 
4.7%
:51
 
4.7%
250
 
4.6%
449
 
4.5%
945
 
4.2%
843
 
4.0%
Other values (4)150
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/357
 
9.8%
t357
 
9.8%
a255
 
7.0%
m255
 
7.0%
p204
 
5.6%
s204
 
5.6%
i204
 
5.6%
.153
 
4.2%
e153
 
4.2%
o153
 
4.2%
Other values (22)1335
36.8%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING

Distinct40
Distinct (%)78.4%
Missing3
Missing (%)5.6%
Memory size560.0 B
https://static.tvmaze.com/uploads/images/original_untouched/381/954567.jpg
https://static.tvmaze.com/uploads/images/original_untouched/416/1040572.jpg
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/291/729461.jpg
 
2
Other values (35)
35 

Length

Max length75
Median length74
Mean length74.17647059
Min length73

Characters and Unicode

Total characters3783
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)68.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713049.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/381/954567.jpg6
 
11.1%
https://static.tvmaze.com/uploads/images/original_untouched/416/1040572.jpg4
 
7.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729461.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713049.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/389/973148.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/287/718562.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/729040.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/408/1021576.jpg1
 
1.9%
Other values (30)30
55.6%
(Missing)3
 
5.6%

Length

2022-09-04T23:42:50.772250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/381/954567.jpg6
 
11.8%
https://static.tvmaze.com/uploads/images/original_untouched/416/1040572.jpg4
 
7.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/729461.jpg2
 
3.9%
https://static.tvmaze.com/uploads/images/original_untouched/412/1031049.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/717764.jpg1
 
2.0%
Other values (30)30
58.8%

Most occurring characters

ValueCountFrequency (%)
/357
 
9.4%
t306
 
8.1%
a255
 
6.7%
s204
 
5.4%
i204
 
5.4%
o204
 
5.4%
p153
 
4.0%
c153
 
4.0%
.153
 
4.0%
g153
 
4.0%
Other values (23)1641
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2703
71.5%
Other Punctuation561
 
14.8%
Decimal Number468
 
12.4%
Connector Punctuation51
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t306
 
11.3%
a255
 
9.4%
s204
 
7.5%
i204
 
7.5%
o204
 
7.5%
p153
 
5.7%
c153
 
5.7%
g153
 
5.7%
m153
 
5.7%
e153
 
5.7%
Other values (9)765
28.3%
Decimal Number
ValueCountFrequency (%)
173
15.6%
758
12.4%
250
10.7%
449
10.5%
945
9.6%
843
9.2%
043
9.2%
542
9.0%
634
7.3%
331
6.6%
Other Punctuation
ValueCountFrequency (%)
/357
63.6%
.153
27.3%
:51
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2703
71.5%
Common1080
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t306
 
11.3%
a255
 
9.4%
s204
 
7.5%
i204
 
7.5%
o204
 
7.5%
p153
 
5.7%
c153
 
5.7%
g153
 
5.7%
m153
 
5.7%
e153
 
5.7%
Other values (9)765
28.3%
Common
ValueCountFrequency (%)
/357
33.1%
.153
14.2%
173
 
6.8%
758
 
5.4%
:51
 
4.7%
_51
 
4.7%
250
 
4.6%
449
 
4.5%
945
 
4.2%
843
 
4.0%
Other values (4)150
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3783
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/357
 
9.4%
t306
 
8.1%
a255
 
6.7%
s204
 
5.4%
i204
 
5.4%
o204
 
5.4%
p153
 
4.0%
c153
 
4.0%
.153
 
4.0%
g153
 
4.0%
Other values (23)1641
43.4%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct41
Distinct (%)78.8%
Missing2
Missing (%)3.7%
Memory size560.0 B
<p>Norwegian documentary show about people that have settled in remote areas, a mountain shelf, a mountain cabin or a remote area deep into the wilderness.</p>
<p>Thomas Becker, son of a powerful building contractor, is shot on New Year's Day. Commissioner Barbara Falck and colleague Christian Krämer start the investigation and suspect a connection with the collapse of the "cube", in which a young cleaner was killed. Was the murder of Thomas an act of revenge against the Becker &amp; Sons company?</p>
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>
 
2
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
 
2
<p>Ju Xuanwen (Wan Yan Lo-yun) is a man with a noble appearance and many virtues. It is a pity that he fell ill with neurosis at a young age - after an unexplained car accident he falls into a delusional state and considers himself a prince. Since then, he no longer cares about the activities of his company and concentrates on becoming emperor.<br />Lo Huai (Chuang Da Fei) - psychiatrist on the verge of bankruptcy. Because of the need for money, she took responsibility for the treatment of Ju Xuanwen. However, she did not expect her peaceful days to end one day. Spending time together, they began to fall in love with each other.</p>
 
2
Other values (36)
36 

Length

Max length913
Median length411
Mean length353.2115385
Min length96

Characters and Unicode

Total characters18367
Distinct characters101
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)69.2%

Sample

1st row<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>
2nd row<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>
3rd row<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p>Norwegian documentary show about people that have settled in remote areas, a mountain shelf, a mountain cabin or a remote area deep into the wilderness.</p>6
 
11.1%
<p>Thomas Becker, son of a powerful building contractor, is shot on New Year's Day. Commissioner Barbara Falck and colleague Christian Krämer start the investigation and suspect a connection with the collapse of the "cube", in which a young cleaner was killed. Was the murder of Thomas an act of revenge against the Becker &amp; Sons company?</p>4
 
7.4%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
3.7%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
3.7%
<p>Ju Xuanwen (Wan Yan Lo-yun) is a man with a noble appearance and many virtues. It is a pity that he fell ill with neurosis at a young age - after an unexplained car accident he falls into a delusional state and considers himself a prince. Since then, he no longer cares about the activities of his company and concentrates on becoming emperor.<br />Lo Huai (Chuang Da Fei) - psychiatrist on the verge of bankruptcy. Because of the need for money, she took responsibility for the treatment of Ju Xuanwen. However, she did not expect her peaceful days to end one day. Spending time together, they began to fall in love with each other.</p>2
 
3.7%
<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>1
 
1.9%
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>1
 
1.9%
<p><b>The George Lucas Talk Show</b>, a long-running cult talk show hosted by Connor Ratliff, as George Lucas, his sidekick Watto (Griffin Newman), and his producer Patrick Cotnoir. They interview guests in a panel format weekly on PlanetScum.</p>1
 
1.9%
<p>A show of intellectual satire. The show discusses national and foreign issues in a witty and biting way, and once a month - a topic prepared in detail by the screenwriters. Since the beginning of the fifth season, three hosts have shared the main wheel: Andrius Tapinas, Ignas Grinevičius, and Irma Bogdanovičiūtė.</p>1
 
1.9%
<p>Are ghosts and demons dwelling among us? The Fourman Brothers, a family of paranormal investigators, investigate hauntings.</p>1
 
1.9%
Other values (31)31
57.4%
(Missing)2
 
3.7%

Length

2022-09-04T23:42:50.879159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the192
 
6.3%
a111
 
3.7%
and98
 
3.2%
of96
 
3.2%
to65
 
2.1%
in63
 
2.1%
is34
 
1.1%
with32
 
1.1%
his32
 
1.1%
that23
 
0.8%
Other values (1143)2290
75.4%

Most occurring characters

ValueCountFrequency (%)
2978
16.2%
e1709
 
9.3%
a1207
 
6.6%
t1197
 
6.5%
n1087
 
5.9%
o1060
 
5.8%
i1001
 
5.4%
r884
 
4.8%
s878
 
4.8%
h701
 
3.8%
Other values (91)5665
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter13874
75.5%
Space Separator2985
 
16.3%
Uppercase Letter562
 
3.1%
Other Punctuation513
 
2.8%
Math Symbol320
 
1.7%
Dash Punctuation40
 
0.2%
Decimal Number40
 
0.2%
Open Punctuation10
 
0.1%
Close Punctuation10
 
0.1%
Other Letter8
 
< 0.1%
Other values (3)5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1709
12.3%
a1207
 
8.7%
t1197
 
8.6%
n1087
 
7.8%
o1060
 
7.6%
i1001
 
7.2%
r884
 
6.4%
s878
 
6.3%
h701
 
5.1%
l517
 
3.7%
Other values (21)3633
26.2%
Uppercase Letter
ValueCountFrequency (%)
T59
 
10.5%
S51
 
9.1%
A31
 
5.5%
W31
 
5.5%
C29
 
5.2%
F26
 
4.6%
J26
 
4.6%
I24
 
4.3%
N24
 
4.3%
M21
 
3.7%
Other values (16)240
42.7%
Other Punctuation
ValueCountFrequency (%)
,177
34.5%
.144
28.1%
/85
16.6%
'32
 
6.2%
"31
 
6.0%
!13
 
2.5%
?11
 
2.1%
:10
 
1.9%
;4
 
0.8%
&4
 
0.8%
Other values (2)2
 
0.4%
Decimal Number
ValueCountFrequency (%)
011
27.5%
110
25.0%
27
17.5%
44
 
10.0%
92
 
5.0%
52
 
5.0%
72
 
5.0%
31
 
2.5%
81
 
2.5%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Dash Punctuation
ValueCountFrequency (%)
-31
77.5%
8
 
20.0%
1
 
2.5%
Space Separator
ValueCountFrequency (%)
2978
99.8%
 7
 
0.2%
Math Symbol
ValueCountFrequency (%)
<160
50.0%
>160
50.0%
Open Punctuation
ValueCountFrequency (%)
(9
90.0%
[1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
)9
90.0%
]1
 
10.0%
Currency Symbol
ValueCountFrequency (%)
$2
66.7%
1
33.3%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14436
78.6%
Common3923
 
21.4%
Katakana4
 
< 0.1%
Han4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1709
11.8%
a1207
 
8.4%
t1197
 
8.3%
n1087
 
7.5%
o1060
 
7.3%
i1001
 
6.9%
r884
 
6.1%
s878
 
6.1%
h701
 
4.9%
l517
 
3.6%
Other values (47)4195
29.1%
Common
ValueCountFrequency (%)
2978
75.9%
,177
 
4.5%
<160
 
4.1%
>160
 
4.1%
.144
 
3.7%
/85
 
2.2%
'32
 
0.8%
"31
 
0.8%
-31
 
0.8%
!13
 
0.3%
Other values (26)112
 
2.9%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18331
99.8%
None16
 
0.1%
Punctuation9
 
< 0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%
Currency Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2978
16.2%
e1709
 
9.3%
a1207
 
6.6%
t1197
 
6.5%
n1087
 
5.9%
o1060
 
5.8%
i1001
 
5.5%
r884
 
4.8%
s878
 
4.8%
h701
 
3.8%
Other values (72)5629
30.7%
Punctuation
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
None
ValueCountFrequency (%)
 7
43.8%
ä4
25.0%
č2
 
12.5%
ā1
 
6.2%
ė1
 
6.2%
ū1
 
6.2%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639838179
Minimum1603467037
Maximum1662237273
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2022-09-04T23:42:50.975275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1603467037
5-th percentile1610541549
Q11622281809
median1642793354
Q31655103422
95-th percentile1661984441
Maximum1662237273
Range58770236
Interquartile range (IQR)32821613.25

Descriptive statistics

Standard deviation18247605.79
Coefficient of variation (CV)0.01112768688
Kurtosis-1.222061018
Mean1639838179
Median Absolute Deviation (MAD)15724727.5
Skewness-0.4260646216
Sum8.855126165 × 1010
Variance3.329751171 × 1014
MonotonicityNot monotonic
2022-09-04T23:42:51.060287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
16389931946
 
11.1%
16585180814
 
7.4%
16549764112
 
3.7%
16184666822
 
3.7%
16154510692
 
3.7%
16620301001
 
1.9%
16470729551
 
1.9%
16532523561
 
1.9%
16182435821
 
1.9%
16612645191
 
1.9%
Other values (33)33
61.1%
ValueCountFrequency (%)
16034670371
1.9%
16085040201
1.9%
16096167881
1.9%
16110394971
1.9%
16114368421
1.9%
16120609221
1.9%
16149309731
1.9%
16154510692
3.7%
16182435821
1.9%
16184666822
3.7%
ValueCountFrequency (%)
16622372731
 
1.9%
16622069171
 
1.9%
16620301001
 
1.9%
16619598561
 
1.9%
16612645191
 
1.9%
16612547171
 
1.9%
16611076721
 
1.9%
16598778421
 
1.9%
16585180814
7.4%
16574892271
 
1.9%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
https://api.tvmaze.com/shows/33172
https://api.tvmaze.com/shows/63155
https://api.tvmaze.com/shows/52743
 
2
https://api.tvmaze.com/shows/54762
 
2
https://api.tvmaze.com/shows/52781
 
2
Other values (38)
38 

Length

Max length34
Median length34
Mean length33.98148148
Min length33

Characters and Unicode

Total characters1835
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://api.tvmaze.com/shows/48683
2nd rowhttps://api.tvmaze.com/shows/51471
3rd rowhttps://api.tvmaze.com/shows/52178
4th rowhttps://api.tvmaze.com/shows/54033
5th rowhttps://api.tvmaze.com/shows/50398

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/331726
 
11.1%
https://api.tvmaze.com/shows/631554
 
7.4%
https://api.tvmaze.com/shows/527432
 
3.7%
https://api.tvmaze.com/shows/547622
 
3.7%
https://api.tvmaze.com/shows/527812
 
3.7%
https://api.tvmaze.com/shows/486831
 
1.9%
https://api.tvmaze.com/shows/599511
 
1.9%
https://api.tvmaze.com/shows/523031
 
1.9%
https://api.tvmaze.com/shows/527371
 
1.9%
https://api.tvmaze.com/shows/528581
 
1.9%
Other values (33)33
61.1%

Length

2022-09-04T23:42:51.162020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/331726
 
11.1%
https://api.tvmaze.com/shows/631554
 
7.4%
https://api.tvmaze.com/shows/527432
 
3.7%
https://api.tvmaze.com/shows/547622
 
3.7%
https://api.tvmaze.com/shows/527812
 
3.7%
https://api.tvmaze.com/shows/495241
 
1.9%
https://api.tvmaze.com/shows/521781
 
1.9%
https://api.tvmaze.com/shows/540331
 
1.9%
https://api.tvmaze.com/shows/503981
 
1.9%
https://api.tvmaze.com/shows/402401
 
1.9%
Other values (33)33
61.1%

Most occurring characters

ValueCountFrequency (%)
/216
 
11.8%
s162
 
8.8%
t162
 
8.8%
h108
 
5.9%
p108
 
5.9%
a108
 
5.9%
o108
 
5.9%
.108
 
5.9%
m108
 
5.9%
e54
 
2.9%
Other values (16)593
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1188
64.7%
Other Punctuation378
 
20.6%
Decimal Number269
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s162
13.6%
t162
13.6%
h108
9.1%
p108
9.1%
a108
9.1%
o108
9.1%
m108
9.1%
e54
 
4.5%
w54
 
4.5%
c54
 
4.5%
Other values (3)162
13.6%
Decimal Number
ValueCountFrequency (%)
545
16.7%
341
15.2%
234
12.6%
429
10.8%
127
10.0%
724
8.9%
821
7.8%
618
 
6.7%
916
 
5.9%
014
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/216
57.1%
.108
28.6%
:54
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1188
64.7%
Common647
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/216
33.4%
.108
16.7%
:54
 
8.3%
545
 
7.0%
341
 
6.3%
234
 
5.3%
429
 
4.5%
127
 
4.2%
724
 
3.7%
821
 
3.2%
Other values (3)48
 
7.4%
Latin
ValueCountFrequency (%)
s162
13.6%
t162
13.6%
h108
9.1%
p108
9.1%
a108
9.1%
o108
9.1%
m108
9.1%
e54
 
4.5%
w54
 
4.5%
c54
 
4.5%
Other values (3)162
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/216
 
11.8%
s162
 
8.8%
t162
 
8.8%
h108
 
5.9%
p108
 
5.9%
a108
 
5.9%
o108
 
5.9%
.108
 
5.9%
m108
 
5.9%
e54
 
2.9%
Other values (16)593
32.3%
Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size560.0 B
https://api.tvmaze.com/episodes/2227997
https://api.tvmaze.com/episodes/2363744
https://api.tvmaze.com/episodes/1997552
 
2
https://api.tvmaze.com/episodes/2071494
 
2
https://api.tvmaze.com/episodes/1998564
 
2
Other values (38)
38 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2106
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://api.tvmaze.com/episodes/2383519
2nd rowhttps://api.tvmaze.com/episodes/1956341
3rd rowhttps://api.tvmaze.com/episodes/2259040
4th rowhttps://api.tvmaze.com/episodes/2309441
5th rowhttps://api.tvmaze.com/episodes/2012327

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22279976
 
11.1%
https://api.tvmaze.com/episodes/23637444
 
7.4%
https://api.tvmaze.com/episodes/19975522
 
3.7%
https://api.tvmaze.com/episodes/20714942
 
3.7%
https://api.tvmaze.com/episodes/19985642
 
3.7%
https://api.tvmaze.com/episodes/23835191
 
1.9%
https://api.tvmaze.com/episodes/22559551
 
1.9%
https://api.tvmaze.com/episodes/23321741
 
1.9%
https://api.tvmaze.com/episodes/20564141
 
1.9%
https://api.tvmaze.com/episodes/23780191
 
1.9%
Other values (33)33
61.1%

Length

2022-09-04T23:42:51.234949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22279976
 
11.1%
https://api.tvmaze.com/episodes/23637444
 
7.4%
https://api.tvmaze.com/episodes/19975522
 
3.7%
https://api.tvmaze.com/episodes/20714942
 
3.7%
https://api.tvmaze.com/episodes/19985642
 
3.7%
https://api.tvmaze.com/episodes/19780171
 
1.9%
https://api.tvmaze.com/episodes/22590401
 
1.9%
https://api.tvmaze.com/episodes/23094411
 
1.9%
https://api.tvmaze.com/episodes/20123271
 
1.9%
https://api.tvmaze.com/episodes/19565181
 
1.9%
Other values (33)33
61.1%

Most occurring characters

ValueCountFrequency (%)
/216
 
10.3%
t162
 
7.7%
p162
 
7.7%
s162
 
7.7%
e162
 
7.7%
a108
 
5.1%
i108
 
5.1%
.108
 
5.1%
m108
 
5.1%
o108
 
5.1%
Other values (16)702
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1350
64.1%
Other Punctuation378
 
17.9%
Decimal Number378
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t162
12.0%
p162
12.0%
s162
12.0%
e162
12.0%
a108
8.0%
i108
8.0%
m108
8.0%
o108
8.0%
h54
 
4.0%
d54
 
4.0%
Other values (3)162
12.0%
Decimal Number
ValueCountFrequency (%)
272
19.0%
950
13.2%
745
11.9%
144
11.6%
336
9.5%
433
8.7%
529
7.7%
627
 
7.1%
021
 
5.6%
821
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/216
57.1%
.108
28.6%
:54
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1350
64.1%
Common756
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/216
28.6%
.108
14.3%
272
 
9.5%
:54
 
7.1%
950
 
6.6%
745
 
6.0%
144
 
5.8%
336
 
4.8%
433
 
4.4%
529
 
3.8%
Other values (3)69
 
9.1%
Latin
ValueCountFrequency (%)
t162
12.0%
p162
12.0%
s162
12.0%
e162
12.0%
a108
8.0%
i108
8.0%
m108
8.0%
o108
8.0%
h54
 
4.0%
d54
 
4.0%
Other values (3)162
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/216
 
10.3%
t162
 
7.7%
p162
 
7.7%
s162
 
7.7%
e162
 
7.7%
a108
 
5.1%
i108
 
5.1%
.108
 
5.1%
m108
 
5.1%
o108
 
5.1%
Other values (16)702
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
https://api.tvmaze.com/episodes/2259041
https://api.tvmaze.com/episodes/2309442
https://api.tvmaze.com/episodes/2377389
https://api.tvmaze.com/episodes/2371586
https://api.tvmaze.com/episodes/2348846

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2259041
2nd rowhttps://api.tvmaze.com/episodes/2309442
3rd rowhttps://api.tvmaze.com/episodes/2377389
4th rowhttps://api.tvmaze.com/episodes/2371586
5th rowhttps://api.tvmaze.com/episodes/2348846

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
 
1.9%
https://api.tvmaze.com/episodes/23094421
 
1.9%
https://api.tvmaze.com/episodes/23773891
 
1.9%
https://api.tvmaze.com/episodes/23715861
 
1.9%
https://api.tvmaze.com/episodes/23488461
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:51.305949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:51.386018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
20.0%
https://api.tvmaze.com/episodes/23094421
20.0%
https://api.tvmaze.com/episodes/23773891
20.0%
https://api.tvmaze.com/episodes/23715861
20.0%
https://api.tvmaze.com/episodes/23488461
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
27
20.0%
35
14.3%
45
14.3%
84
11.4%
93
8.6%
73
8.6%
52
 
5.7%
02
 
5.7%
12
 
5.7%
62
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
27
 
10.0%
35
 
7.1%
45
 
7.1%
:5
 
7.1%
84
 
5.7%
93
 
4.3%
73
 
4.3%
52
 
2.9%
Other values (3)6
 
8.6%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct16
Distinct (%)100.0%
Missing38
Missing (%)70.4%
Memory size560.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041810.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/401/1003458.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/285/714233.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/389/973510.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/729936.jpg
 
1
Other values (11)
11 

Length

Max length73
Median length72
Mean length72.375
Min length72

Characters and Unicode

Total characters1158
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724756.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726354.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/291/729727.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721859.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/401/1003923.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041810.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/401/1003458.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714233.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/389/973510.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729936.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/310/776221.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724940.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041809.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724756.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041808.jpg1
 
1.9%
Other values (6)6
 
11.1%
(Missing)38
70.4%

Length

2022-09-04T23:42:51.475187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041810.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/401/1003458.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714233.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/389/973510.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729936.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/310/776221.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724940.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041809.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724756.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/416/1041808.jpg1
 
6.2%
Other values (6)6
37.5%

Most occurring characters

ValueCountFrequency (%)
/112
 
9.7%
a96
 
8.3%
s80
 
6.9%
m80
 
6.9%
t80
 
6.9%
p64
 
5.5%
e64
 
5.5%
i48
 
4.1%
c48
 
4.1%
.48
 
4.1%
Other values (22)438
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter816
70.5%
Other Punctuation176
 
15.2%
Decimal Number150
 
13.0%
Connector Punctuation16
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a96
11.8%
s80
9.8%
m80
9.8%
t80
9.8%
p64
 
7.8%
e64
 
7.8%
i48
 
5.9%
c48
 
5.9%
d48
 
5.9%
l32
 
3.9%
Other values (8)176
21.6%
Decimal Number
ValueCountFrequency (%)
125
16.7%
219
12.7%
018
12.0%
417
11.3%
815
10.0%
915
10.0%
714
9.3%
311
7.3%
68
 
5.3%
58
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/112
63.6%
.48
27.3%
:16
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin816
70.5%
Common342
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a96
11.8%
s80
9.8%
m80
9.8%
t80
9.8%
p64
 
7.8%
e64
 
7.8%
i48
 
5.9%
c48
 
5.9%
d48
 
5.9%
l32
 
3.9%
Other values (8)176
21.6%
Common
ValueCountFrequency (%)
/112
32.7%
.48
14.0%
125
 
7.3%
219
 
5.6%
018
 
5.3%
417
 
5.0%
_16
 
4.7%
:16
 
4.7%
815
 
4.4%
915
 
4.4%
Other values (4)41
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/112
 
9.7%
a96
 
8.3%
s80
 
6.9%
m80
 
6.9%
t80
 
6.9%
p64
 
5.5%
e64
 
5.5%
i48
 
4.1%
c48
 
4.1%
.48
 
4.1%
Other values (22)438
37.8%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct16
Distinct (%)100.0%
Missing38
Missing (%)70.4%
Memory size560.0 B
https://static.tvmaze.com/uploads/images/original_untouched/416/1041810.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/401/1003458.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/285/714233.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/389/973510.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/729936.jpg
 
1
Other values (11)
11 

Length

Max length75
Median length74
Mean length74.375
Min length74

Characters and Unicode

Total characters1190
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/724756.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726354.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/291/729727.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721859.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/401/1003923.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/416/1041810.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/401/1003458.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/285/714233.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/389/973510.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/729936.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/310/776221.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/724940.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/416/1041809.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/724756.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/416/1041808.jpg1
 
1.9%
Other values (6)6
 
11.1%
(Missing)38
70.4%

Length

2022-09-04T23:42:51.550302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/416/1041810.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/401/1003458.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/714233.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/389/973510.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/291/729936.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/310/776221.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/724940.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/416/1041809.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/724756.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/416/1041808.jpg1
 
6.2%
Other values (6)6
37.5%

Most occurring characters

ValueCountFrequency (%)
/112
 
9.4%
t96
 
8.1%
a80
 
6.7%
s64
 
5.4%
i64
 
5.4%
o64
 
5.4%
p48
 
4.0%
c48
 
4.0%
.48
 
4.0%
g48
 
4.0%
Other values (23)518
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter848
71.3%
Other Punctuation176
 
14.8%
Decimal Number150
 
12.6%
Connector Punctuation16
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t96
 
11.3%
a80
 
9.4%
s64
 
7.5%
i64
 
7.5%
o64
 
7.5%
p48
 
5.7%
c48
 
5.7%
g48
 
5.7%
m48
 
5.7%
e48
 
5.7%
Other values (9)240
28.3%
Decimal Number
ValueCountFrequency (%)
125
16.7%
219
12.7%
018
12.0%
417
11.3%
815
10.0%
915
10.0%
714
9.3%
311
7.3%
68
 
5.3%
58
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/112
63.6%
.48
27.3%
:16
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin848
71.3%
Common342
28.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t96
 
11.3%
a80
 
9.4%
s64
 
7.5%
i64
 
7.5%
o64
 
7.5%
p48
 
5.7%
c48
 
5.7%
g48
 
5.7%
m48
 
5.7%
e48
 
5.7%
Other values (9)240
28.3%
Common
ValueCountFrequency (%)
/112
32.7%
.48
14.0%
125
 
7.3%
219
 
5.6%
018
 
5.3%
417
 
5.0%
:16
 
4.7%
_16
 
4.7%
815
 
4.4%
915
 
4.4%
Other values (4)41
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/112
 
9.4%
t96
 
8.1%
a80
 
6.7%
s64
 
5.4%
i64
 
5.4%
o64
 
5.4%
p48
 
4.0%
c48
 
4.0%
.48
 
4.0%
g48
 
4.0%
Other values (23)518
43.5%

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
8.0
1320.0
374.0
132.0
91.0

Length

Max length6
Median length5
Mean length4.6
Min length3

Characters and Unicode

Total characters23
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row8.0
2nd row1320.0
3rd row374.0
4th row132.0
5th row91.0

Common Values

ValueCountFrequency (%)
8.01
 
1.9%
1320.01
 
1.9%
374.01
 
1.9%
132.01
 
1.9%
91.01
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:51.632950image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:51.726224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
8.01
20.0%
1320.01
20.0%
374.01
20.0%
132.01
20.0%
91.01
20.0%

Most occurring characters

ValueCountFrequency (%)
06
26.1%
.5
21.7%
13
13.0%
33
13.0%
22
 
8.7%
81
 
4.3%
71
 
4.3%
41
 
4.3%
91
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18
78.3%
Other Punctuation5
 
21.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
06
33.3%
13
16.7%
33
16.7%
22
 
11.1%
81
 
5.6%
71
 
5.6%
41
 
5.6%
91
 
5.6%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
06
26.1%
.5
21.7%
13
13.0%
33
13.0%
22
 
8.7%
81
 
4.3%
71
 
4.3%
41
 
4.3%
91
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
06
26.1%
.5
21.7%
13
13.0%
33
13.0%
22
 
8.7%
81
 
4.3%
71
 
4.3%
41
 
4.3%
91
 
4.3%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
HBO
UA:Перший
TV Globo
Tokyo MX
NRK1

Length

Max length9
Median length8
Mean length6.4
Min length3

Characters and Unicode

Total characters32
Distinct characters27
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowHBO
2nd rowUA:Перший
3rd rowTV Globo
4th rowTokyo MX
5th rowNRK1

Common Values

ValueCountFrequency (%)
HBO1
 
1.9%
UA:Перший1
 
1.9%
TV Globo1
 
1.9%
Tokyo MX1
 
1.9%
NRK11
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:51.812339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:51.890280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
hbo1
14.3%
ua:перший1
14.3%
tv1
14.3%
globo1
14.3%
tokyo1
14.3%
mx1
14.3%
nrk11
14.3%

Most occurring characters

ValueCountFrequency (%)
o4
 
12.5%
2
 
6.2%
T2
 
6.2%
H1
 
3.1%
K1
 
3.1%
R1
 
3.1%
N1
 
3.1%
X1
 
3.1%
M1
 
3.1%
y1
 
3.1%
Other values (17)17
53.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter15
46.9%
Lowercase Letter13
40.6%
Space Separator2
 
6.2%
Other Punctuation1
 
3.1%
Decimal Number1
 
3.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T2
13.3%
H1
 
6.7%
K1
 
6.7%
R1
 
6.7%
N1
 
6.7%
X1
 
6.7%
M1
 
6.7%
G1
 
6.7%
V1
 
6.7%
B1
 
6.7%
Other values (4)4
26.7%
Lowercase Letter
ValueCountFrequency (%)
o4
30.8%
y1
 
7.7%
k1
 
7.7%
b1
 
7.7%
l1
 
7.7%
й1
 
7.7%
и1
 
7.7%
ш1
 
7.7%
р1
 
7.7%
е1
 
7.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
:1
100.0%
Decimal Number
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22
68.8%
Cyrillic6
 
18.8%
Common4
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o4
18.2%
T2
 
9.1%
H1
 
4.5%
K1
 
4.5%
R1
 
4.5%
N1
 
4.5%
X1
 
4.5%
M1
 
4.5%
y1
 
4.5%
k1
 
4.5%
Other values (8)8
36.4%
Cyrillic
ValueCountFrequency (%)
й1
16.7%
и1
16.7%
ш1
16.7%
р1
16.7%
е1
16.7%
П1
16.7%
Common
ValueCountFrequency (%)
2
50.0%
:1
25.0%
11
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII26
81.2%
Cyrillic6
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o4
 
15.4%
2
 
7.7%
T2
 
7.7%
H1
 
3.8%
K1
 
3.8%
R1
 
3.8%
N1
 
3.8%
X1
 
3.8%
M1
 
3.8%
y1
 
3.8%
Other values (11)11
42.3%
Cyrillic
ValueCountFrequency (%)
й1
16.7%
и1
16.7%
ш1
16.7%
р1
16.7%
е1
16.7%
П1
16.7%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
United States
Ukraine
Brazil
Japan
Norway

Length

Max length13
Median length7
Mean length7.4
Min length5

Characters and Unicode

Total characters37
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowUnited States
2nd rowUkraine
3rd rowBrazil
4th rowJapan
5th rowNorway

Common Values

ValueCountFrequency (%)
United States1
 
1.9%
Ukraine1
 
1.9%
Brazil1
 
1.9%
Japan1
 
1.9%
Norway1
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:51.965458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.167363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
united1
16.7%
states1
16.7%
ukraine1
16.7%
brazil1
16.7%
japan1
16.7%
norway1
16.7%

Most occurring characters

ValueCountFrequency (%)
a6
16.2%
i3
 
8.1%
t3
 
8.1%
e3
 
8.1%
n3
 
8.1%
r3
 
8.1%
U2
 
5.4%
l1
 
2.7%
w1
 
2.7%
o1
 
2.7%
Other values (11)11
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30
81.1%
Uppercase Letter6
 
16.2%
Space Separator1
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a6
20.0%
i3
10.0%
t3
10.0%
e3
10.0%
n3
10.0%
r3
10.0%
l1
 
3.3%
w1
 
3.3%
o1
 
3.3%
p1
 
3.3%
Other values (5)5
16.7%
Uppercase Letter
ValueCountFrequency (%)
U2
33.3%
N1
16.7%
J1
16.7%
B1
16.7%
S1
16.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin36
97.3%
Common1
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a6
16.7%
i3
 
8.3%
t3
 
8.3%
e3
 
8.3%
n3
 
8.3%
r3
 
8.3%
U2
 
5.6%
l1
 
2.8%
w1
 
2.8%
o1
 
2.8%
Other values (10)10
27.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a6
16.2%
i3
 
8.1%
t3
 
8.1%
e3
 
8.1%
n3
 
8.1%
r3
 
8.1%
U2
 
5.4%
l1
 
2.7%
w1
 
2.7%
o1
 
2.7%
Other values (11)11
29.7%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
US
UA
BR
JP
NO

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowUS
2nd rowUA
3rd rowBR
4th rowJP
5th rowNO

Common Values

ValueCountFrequency (%)
US1
 
1.9%
UA1
 
1.9%
BR1
 
1.9%
JP1
 
1.9%
NO1
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:52.270411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.351545image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
us1
20.0%
ua1
20.0%
br1
20.0%
jp1
20.0%
no1
20.0%

Most occurring characters

ValueCountFrequency (%)
U2
20.0%
S1
10.0%
A1
10.0%
B1
10.0%
R1
10.0%
J1
10.0%
P1
10.0%
N1
10.0%
O1
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U2
20.0%
S1
10.0%
A1
10.0%
B1
10.0%
R1
10.0%
J1
10.0%
P1
10.0%
N1
10.0%
O1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U2
20.0%
S1
10.0%
A1
10.0%
B1
10.0%
R1
10.0%
J1
10.0%
P1
10.0%
N1
10.0%
O1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U2
20.0%
S1
10.0%
A1
10.0%
B1
10.0%
R1
10.0%
J1
10.0%
P1
10.0%
N1
10.0%
O1
10.0%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing49
Missing (%)90.7%
Memory size560.0 B
America/New_York
Europe/Zaporozhye
America/Noronha
Asia/Tokyo
Europe/Oslo

Length

Max length17
Median length15
Mean length13.8
Min length10

Characters and Unicode

Total characters69
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowAmerica/New_York
2nd rowEurope/Zaporozhye
3rd rowAmerica/Noronha
4th rowAsia/Tokyo
5th rowEurope/Oslo

Common Values

ValueCountFrequency (%)
America/New_York1
 
1.9%
Europe/Zaporozhye1
 
1.9%
America/Noronha1
 
1.9%
Asia/Tokyo1
 
1.9%
Europe/Oslo1
 
1.9%
(Missing)49
90.7%

Length

2022-09-04T23:42:52.433856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.519856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york1
20.0%
europe/zaporozhye1
20.0%
america/noronha1
20.0%
asia/tokyo1
20.0%
europe/oslo1
20.0%

Most occurring characters

ValueCountFrequency (%)
o10
14.5%
r7
 
10.1%
e6
 
8.7%
a5
 
7.2%
/5
 
7.2%
A3
 
4.3%
i3
 
4.3%
p3
 
4.3%
E2
 
2.9%
s2
 
2.9%
Other values (16)23
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter52
75.4%
Uppercase Letter11
 
15.9%
Other Punctuation5
 
7.2%
Connector Punctuation1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o10
19.2%
r7
13.5%
e6
11.5%
a5
9.6%
i3
 
5.8%
p3
 
5.8%
s2
 
3.8%
y2
 
3.8%
h2
 
3.8%
u2
 
3.8%
Other values (7)10
19.2%
Uppercase Letter
ValueCountFrequency (%)
A3
27.3%
E2
18.2%
N2
18.2%
Y1
 
9.1%
Z1
 
9.1%
T1
 
9.1%
O1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin63
91.3%
Common6
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o10
15.9%
r7
 
11.1%
e6
 
9.5%
a5
 
7.9%
A3
 
4.8%
i3
 
4.8%
p3
 
4.8%
E2
 
3.2%
s2
 
3.2%
y2
 
3.2%
Other values (14)20
31.7%
Common
ValueCountFrequency (%)
/5
83.3%
_1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII69
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o10
14.5%
r7
 
10.1%
e6
 
8.7%
a5
 
7.2%
/5
 
7.2%
A3
 
4.3%
i3
 
4.3%
p3
 
4.3%
E2
 
2.9%
s2
 
2.9%
Other values (16)23
33.3%

_embedded.show.network.officialSite
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing53
Missing (%)98.1%
Memory size560.0 B
https://www.hbo.com/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://www.hbo.com/

Common Values

ValueCountFrequency (%)
https://www.hbo.com/1
 
1.9%
(Missing)53
98.1%

Length

2022-09-04T23:42:52.598856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.668856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.hbo.com1
100.0%

Most occurring characters

ValueCountFrequency (%)
/3
15.0%
w3
15.0%
h2
10.0%
t2
10.0%
.2
10.0%
o2
10.0%
p1
 
5.0%
s1
 
5.0%
:1
 
5.0%
b1
 
5.0%
Other values (2)2
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
70.0%
Other Punctuation6
30.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w3
21.4%
h2
14.3%
t2
14.3%
o2
14.3%
p1
 
7.1%
s1
 
7.1%
b1
 
7.1%
c1
 
7.1%
m1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/3
50.0%
.2
33.3%
:1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin14
70.0%
Common6
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w3
21.4%
h2
14.3%
t2
14.3%
o2
14.3%
p1
 
7.1%
s1
 
7.1%
b1
 
7.1%
c1
 
7.1%
m1
 
7.1%
Common
ValueCountFrequency (%)
/3
50.0%
.2
33.3%
:1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/3
15.0%
w3
15.0%
h2
10.0%
t2
10.0%
.2
10.0%
o2
10.0%
p1
 
5.0%
s1
 
5.0%
:1
 
5.0%
b1
 
5.0%
Other values (2)2
10.0%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing54
Missing (%)100.0%
Memory size560.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing53
Missing (%)98.1%
Memory size560.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
1.9%
(Missing)53
98.1%

Length

2022-09-04T23:42:52.730856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.798856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing53
Missing (%)98.1%
Memory size560.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
1.9%
(Missing)53
98.1%

Length

2022-09-04T23:42:52.858855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:52.926855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing53
Missing (%)98.1%
Memory size560.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
1.9%
(Missing)53
98.1%

Length

2022-09-04T23:42:52.988446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:42:53.061543image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Interactions

2022-09-04T23:42:41.145374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.468272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.445319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.439119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.328560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.425106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:33.571362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.680263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.912308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.858669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.700250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.226532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.686795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.523532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.528563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.419556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.509651image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.017451image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.830213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.993351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.932042image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.972076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.305757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.766068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.702269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.615963image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.506644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.596427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.196847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.974509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.081338image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:38.006485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.134358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.422169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.842186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.777538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.699925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.575779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.679670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.303421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.111180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.152531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:38.095479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.229687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.516979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.920650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.853536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.775921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.656610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.759437image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.451234image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.249287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.256305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:38.331922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.308688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.599047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:28.995645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.927539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.858028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.737672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.842104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.616673image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.319287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.348526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:38.421033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.389697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.682401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.070643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.003004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.930088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.933337image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.910114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.770313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.413356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.432603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:38.952549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.483732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.760528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.151642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.087335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.015695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.018959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:33.001319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:34.935469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.515286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.527667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.172933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.658709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.824668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.221647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.163009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.088292image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.097887image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:33.089137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.098995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.614568image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.598668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.334933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.841575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:42.187177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.292120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.240223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.167491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.186631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:33.168353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.242254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.737302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.691109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.435932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:40.964244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:42.268551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:29.370125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:30.322212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:31.251223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:32.264022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:33.250048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:35.574263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:36.822756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:37.790392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:39.552933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:42:41.061447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-09-04T23:42:53.141553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:42:53.384891image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:42:53.607435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:42:53.860155image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:42:42.811008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:42:43.998871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:42:44.792442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.webChannel.country_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
02053350https://www.tvmaze.com/episodes/2053350/ispoved-1x08-gnojnyjГнойный18.0regular2020-12-2012:002020-12-20T00:00:00+00:0048.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205335048683https://www.tvmaze.com/shows/48683/ispovedИсповедьDocumentaryRussian[]Ended48.047.02020-05-112022-08-30https://premier.one/collections/13412:00[Monday]NaN36NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713049.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713049.jpg<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>1662030100https://api.tvmaze.com/shows/48683https://api.tvmaze.com/episodes/2383519NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11956340https://www.tvmaze.com/episodes/1956340/hero-return-1x11-episode-11Episode 11111.0regular2020-12-2010:002020-12-20T02:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/195634051471https://www.tvmaze.com/shows/51471/hero-returnHero ReturnAnimationChinese[Action, Anime, Science-Fiction]Running15.016.02020-10-18Nonehttps://v.qq.com/detail/q/q72jd29a3oxflsr.html10:00[Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpghttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>1603467037https://api.tvmaze.com/shows/51471https://api.tvmaze.com/episodes/1956341NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21988863https://www.tvmaze.com/episodes/1988863/swallowed-star-1x05-episode-5Episode 515.0regular2020-12-2010:002020-12-20T02:00:00+00:0021.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198886352178https://www.tvmaze.com/shows/52178/swallowed-starSwallowed StarAnimationChinese[Anime, Science-Fiction]RunningNaN21.02020-11-29Nonehttps://v.qq.com/detail/3/324olz7ilvo2j5f.html10:00[Wednesday]7.793NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNone392598.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>1661959856https://api.tvmaze.com/shows/52178https://api.tvmaze.com/episodes/2259040https://api.tvmaze.com/episodes/2259041NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32052510https://www.tvmaze.com/episodes/2052510/wu-shen-zhu-zai-1x85-episode-85Episode 85185.0regular2020-12-2010:002020-12-20T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205251054033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNone379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309441https://api.tvmaze.com/episodes/2309442NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42012322https://www.tvmaze.com/episodes/2012322/mans-diary-2x07-episode-7Episode 727.0regular2020-12-202020-12-20T04:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/201232250398https://www.tvmaze.com/shows/50398/mans-diaryMan's DiaryAnimationChinese[Anime, Supernatural]Running12.012.02019-07-21Nonehttps://www.bilibili.com/bangumi/media/md4314622[Sunday]NaN3NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNone379528.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpghttps://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>1611039497https://api.tvmaze.com/shows/50398https://api.tvmaze.com/episodes/2012327NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52071489https://www.tvmaze.com/episodes/2071489/youths-in-the-breeze-1x19-full-time-sworn-enemy-03FULL-TIME SWORN ENEMY #03119.0regular2020-12-202020-12-20T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207148954762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNone397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62071490https://www.tvmaze.com/episodes/2071490/youths-in-the-breeze-1x20-full-time-sworn-enemy-04FULL-TIME SWORN ENEMY #04120.0regular2020-12-202020-12-20T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207149054762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNone397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71956518https://www.tvmaze.com/episodes/1956518/113-2x10-episode-10Episode 10210.0regular2020-12-2006:002020-12-20T05:00:00+00:0043.0NaNNoneNaNhttps://api.tvmaze.com/episodes/195651840240https://www.tvmaze.com/shows/40240/113113DocumentaryNorwegian[]Ended40.039.02019-01-012020-12-20https://tv.nrk.no/serie/11320:20[Sunday]NaN67NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNone357537.0tt13005000https://static.tvmaze.com/uploads/images/medium_portrait/287/717764.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/717764.jpg<p>What happens when you call 113? In this series we are following the people that are there for us when the worst happens.</p>1657489227https://api.tvmaze.com/shows/40240https://api.tvmaze.com/episodes/1956518NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724756.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724756.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81977328https://www.tvmaze.com/episodes/1977328/stjernestov-1x20-episode-20Episode 20120.0regular2020-12-2006:002020-12-20T05:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197732850752https://www.tvmaze.com/shows/50752/stjernestovStjernestøvScriptedNorwegian[Drama, Children, Family]Ended20.020.02020-12-012020-12-24https://tv.nrk.no/serie/stjernestoev06:00[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN17NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNone392649.0tt11492320https://static.tvmaze.com/uploads/images/medium_portrait/288/721951.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721951.jpg<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>1611436842https://api.tvmaze.com/shows/50752https://api.tvmaze.com/episodes/1977332NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726354.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
91984166https://www.tvmaze.com/episodes/1984166/der-ingen-skulle-tru-at-nokon-kunne-bu-19x01-hovdenHovden191.0regular2020-12-2006:012020-12-20T05:01:00+00:0039.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198416633172https://www.tvmaze.com/shows/33172/der-ingen-skulle-tru-at-nokon-kunne-buDer ingen skulle tru at nokon kunne buDocumentaryNorwegian[Adventure, Travel]RunningNaN34.02002-12-08Nonehttps://tv.nrk.no/serie/der-ingen-skulle-tru-at-nokon-kunne-bu[Sunday]NaN51NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNone85436.0tt5810780https://static.tvmaze.com/uploads/images/medium_portrait/381/954567.jpghttps://static.tvmaze.com/uploads/images/original_untouched/381/954567.jpg<p>Norwegian documentary show about people that have settled in remote areas, a mountain shelf, a mountain cabin or a remote area deep into the wilderness.</p>1638993194https://api.tvmaze.com/shows/33172https://api.tvmaze.com/episodes/2227997NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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